3
%feature("docstring") itk::Functor::BitwiseNot "
5
Performs the C++ unary bitwise NOT operator.
7
C++ includes: itkBitwiseNotFunctor.h
11
%feature("docstring") itk::Functor::DivFloor "
13
Cast arguments to double, performs division then takes the floor.
15
C++ includes: itkDivideFloorFunctor.h
19
%feature("docstring") itk::Functor::DivReal "
21
Promotes arguments to real type and performs division.
23
C++ includes: itkDivideRealFunctor.h
27
%feature("docstring") itk::Functor::UnaryMinus "
28
C++ includes: itkUnaryMinusImageFilter.h
31
%feature("docstring") itk::Functor::UnaryMinus::UnaryMinus "
34
%feature("docstring") itk::Functor::UnaryMinus::~UnaryMinus "
38
%feature("docstring") itk::HashImageFilter "
40
Generates a hash string from an image.
44
This class utlizes low level buffer pointer access, to work with itk::Image and itk::VectorImage. It is modeled after the access an ImageFileWriter provides to an ImageIO.
46
Update in-place on to default after fixing bug in InPlaceImageFilter
49
C++ includes: itkHashImageFilter.h
52
%feature("docstring") itk::HashImageFilter::GetHash "
54
Get the computed Hash values
58
%feature("docstring") itk::HashImageFilter::GetHashOutput "
61
%feature("docstring") itk::HashImageFilter::GetHashOutput "
64
%feature("docstring") itk::HashImageFilter::itkGetMacro "
67
%feature("docstring") itk::HashImageFilter::itkNewMacro "
69
Method for creation through the object factory.
73
%feature("docstring") itk::HashImageFilter::itkSetMacro "
75
Set/Get hashing function as enumerated type
79
%feature("docstring") itk::HashImageFilter::itkTypeMacro "
81
Runtime information support.
85
%feature("docstring") itk::HashImageFilter::MakeOutput "
89
%feature("docstring") itk::ImageIOFactoryRegisterManager "
90
C++ includes: itkImageIOFactoryRegisterManager.h
93
%feature("docstring") itk::ImageIOFactoryRegisterManager::ImageIOFactoryRegisterManager "
96
%feature("docstring") itk::ImageIOFactoryRegisterManager::ImageIOFactoryRegisterManager "
100
%feature("docstring") itk::SliceImageFilter "
102
Slices an image based on a starting index and a stopping index, and a
106
This class is designed to facilitate the implementation of extended
107
sliced based indexing into images.
109
The input and output image must be of the same dimension.
111
The input parameters are a starting and stopping index as well as a
112
stepping size. The staring index indicates the first pixels to used
113
and for each dimension the index is incremented by the step until the
114
index is equal to or \"beyond\" the stopping index. If the step is
115
negative then the image will be revered in the dimension, and the
116
stopping index is expected to be less then the starting index. If the
117
stopping index is already beyond the starting then a image of zero
118
size will be returned.
120
The output image's starting index is always zero. The origin is the
121
physical location of the starting index. The output directions cosine
122
matrix is that of the input but with sign changes matching that of the
126
In certain combination such as with start=1, and step>1 while the
127
physical location of the center of the pixel remains the same, the
128
extent (edge to edge space) of the pixel will beyond the extent of the
132
C++ includes: itkSliceImageFilter.h
135
%feature("docstring") itk::SliceImageFilter::GenerateInputRequestedRegion "
138
%feature("docstring") itk::SliceImageFilter::GenerateOutputInformation "
140
SliceImageFilter produces an image which is a different resolution and with a
141
different pixel spacing than its input image.
143
ProcessObject::GenerateOutputInformaton()
148
%feature("docstring") itk::SliceImageFilter::itkGetConstReferenceMacro "
151
%feature("docstring") itk::SliceImageFilter::itkGetConstReferenceMacro "
154
%feature("docstring") itk::SliceImageFilter::itkGetConstReferenceMacro "
157
%feature("docstring") itk::SliceImageFilter::itkNewMacro "
159
Method for creation through the object factory.
163
%feature("docstring") itk::SliceImageFilter::itkSetMacro "
165
Set/Get the first index extracted from the input image
169
%feature("docstring") itk::SliceImageFilter::itkSetMacro "
171
Set/Get the excluded end of the range
175
%feature("docstring") itk::SliceImageFilter::itkSetMacro "
177
Set/Get the stride of indexes extracted
179
An exception will be generated if 0.
183
%feature("docstring") itk::SliceImageFilter::itkStaticConstMacro "
185
ImageDimension enumeration.
189
%feature("docstring") itk::SliceImageFilter::itkStaticConstMacro "
192
%feature("docstring") itk::SliceImageFilter::itkTypeMacro "
194
Run-time type information (and related methods).
198
%feature("docstring") itk::SliceImageFilter::SetStart "
201
%feature("docstring") itk::SliceImageFilter::SetStep "
204
%feature("docstring") itk::SliceImageFilter::SetStop "
208
%feature("docstring") itk::TransformIOFactoryRegisterManager "
209
C++ includes: itkTransformIOFactoryRegisterManager.h
212
%feature("docstring") itk::TransformIOFactoryRegisterManager::TransformIOFactoryRegisterManager "
215
%feature("docstring") itk::TransformIOFactoryRegisterManager::TransformIOFactoryRegisterManager "
219
%feature("docstring") itk::simple::AbsImageFilter "
221
Computes the absolute value of each pixel.
224
itk::Math::abs() is used to perform the computation.
230
Compute the absolute value of an image
232
itk::simple::Abs for the procedural interface
234
itk::AbsImageFilter for the Doxygen on the original ITK class.
238
C++ includes: sitkAbsImageFilter.h
241
%feature("docstring") itk::simple::AbsImageFilter::AbsImageFilter "
243
Default Constructor that takes no arguments and initializes default
248
%feature("docstring") itk::simple::AbsImageFilter::Execute "
250
Execute the filter on the input image
254
%feature("docstring") itk::simple::AbsImageFilter::GetName "
260
%feature("docstring") itk::simple::AbsImageFilter::ToString "
266
%feature("docstring") itk::simple::AbsImageFilter::~AbsImageFilter "
273
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter "
275
Implements pixel-wise the computation of absolute value difference.
278
This filter is parametrized over the types of the two input images and
279
the type of the output image.
281
Numeric conversions (castings) are done by the C++ defaults.
283
The filter will walk over all the pixels in the two input images, and
284
for each one of them it will do the following:
287
Cast the input 1 pixel value to double .
289
Cast the input 2 pixel value to double .
291
Compute the difference of the two pixel values.
293
Compute the absolute value of the difference.
295
Cast the double value resulting from the absolute value to the pixel
296
type of the output image.
298
Store the casted value into the output image.
299
The filter expects all images to have the same dimension (e.g. all
300
2D, or all 3D, or all ND).
306
Compute the absolute value of the difference of corresponding pixels
309
itk::simple::AbsoluteValueDifference for the procedural interface
311
itk::AbsoluteValueDifferenceImageFilter for the Doxygen on the original ITK class.
315
C++ includes: sitkAbsoluteValueDifferenceImageFilter.h
318
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::AbsoluteValueDifferenceImageFilter "
320
Default Constructor that takes no arguments and initializes default
325
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::Execute "
327
Execute the filter on the input images
331
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::Execute "
333
Execute the filter with an image and a constant
337
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::Execute "
340
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::GetName "
346
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::ToString "
352
%feature("docstring") itk::simple::AbsoluteValueDifferenceImageFilter::~AbsoluteValueDifferenceImageFilter "
359
%feature("docstring") itk::simple::AcosImageFilter "
361
Computes the inverse cosine of each pixel.
364
This filter is templated over the pixel type of the input image and
365
the pixel type of the output image.
367
The filter walks over all the pixels in the input image, and for each
368
pixel does do the following:
371
cast the pixel value to double ,
373
apply the std::acos() function to the double value
375
cast the double value resulting from std::acos() to the pixel type of
378
store the casted value into the output image.
379
The filter expects both images to have the same dimension (e.g. both
380
2D, or both 3D, or both ND).
382
itk::simple::Acos for the procedural interface
384
itk::AcosImageFilter for the Doxygen on the original ITK class.
387
C++ includes: sitkAcosImageFilter.h
390
%feature("docstring") itk::simple::AcosImageFilter::AcosImageFilter "
392
Default Constructor that takes no arguments and initializes default
397
%feature("docstring") itk::simple::AcosImageFilter::Execute "
399
Execute the filter on the input image
403
%feature("docstring") itk::simple::AcosImageFilter::GetName "
409
%feature("docstring") itk::simple::AcosImageFilter::ToString "
415
%feature("docstring") itk::simple::AcosImageFilter::~AcosImageFilter "
422
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter "
424
Power Law Adaptive Histogram Equalization.
427
Histogram equalization modifies the contrast in an image. The AdaptiveHistogramEqualizationImageFilter is a superset of many contrast enhancing filters. By modifying its
428
parameters (alpha, beta, and window), the AdaptiveHistogramEqualizationImageFilter can produce an adaptively equalized histogram or a version of unsharp
429
mask (local mean subtraction). Instead of applying a strict histogram
430
equalization in a window about a pixel, this filter prescribes a
431
mapping function (power law) controlled by the parameters alpha and
434
The parameter alpha controls how much the filter acts like the
435
classical histogram equalization method (alpha=0) to how much the
436
filter acts like an unsharp mask (alpha=1).
438
The parameter beta controls how much the filter acts like an unsharp
439
mask (beta=0) to much the filter acts like pass through (beta=1, with
442
The parameter window controls the size of the region over which local
443
statistics are calculated.
445
By altering alpha, beta and window, a host of equalization and unsharp
446
masking filters is available.
448
The boundary condition ignores the part of the neighborhood outside
449
the image, and over-weights the valid part of the neighborhood.
451
For detail description, reference \"Adaptive Image Contrast
452
Enhancement using Generalizations of Histogram Equalization.\" J.Alex
453
Stark. IEEE Transactions on Image Processing, May 2000.
459
Adaptive histogram equalization
461
itk::simple::AdaptiveHistogramEqualization for the procedural interface
463
itk::AdaptiveHistogramEqualizationImageFilter for the Doxygen on the original ITK class.
467
C++ includes: sitkAdaptiveHistogramEqualizationImageFilter.h
470
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::AdaptiveHistogramEqualizationImageFilter "
472
Default Constructor that takes no arguments and initializes default
477
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::Execute "
479
Execute the filter on the input image
483
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::Execute "
485
Execute the filter on the input image with the given parameters
489
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::GetAlpha "
491
Set/Get the value of alpha. Alpha = 0 produces the adaptive histogram
492
equalization (provided beta=0). Alpha = 1 produces an unsharp mask.
497
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::GetBeta "
499
Set/Get the value of beta. If beta = 1 (and alpha = 1), then the
500
output image matches the input image. As beta approaches 0, the filter
501
behaves as an unsharp mask. Default is 0.3.
505
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::GetName "
511
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::GetRadius "
514
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::GetUseLookupTable "
516
Set/Get whether an optimized lookup table for the intensity mapping
517
function is used. Default is off. Deprecated
521
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::SetAlpha "
523
Set/Get the value of alpha. Alpha = 0 produces the adaptive histogram
524
equalization (provided beta=0). Alpha = 1 produces an unsharp mask.
529
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::SetBeta "
531
Set/Get the value of beta. If beta = 1 (and alpha = 1), then the
532
output image matches the input image. As beta approaches 0, the filter
533
behaves as an unsharp mask. Default is 0.3.
537
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::SetRadius "
540
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::SetRadius "
542
Set the values of the Radius vector all to value
546
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::SetUseLookupTable "
548
Set/Get whether an optimized lookup table for the intensity mapping
549
function is used. Default is off. Deprecated
553
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::ToString "
559
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::UseLookupTableOff "
562
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::UseLookupTableOn "
564
Set the value of UseLookupTable to true or false respectfully.
568
%feature("docstring") itk::simple::AdaptiveHistogramEqualizationImageFilter::~AdaptiveHistogramEqualizationImageFilter "
575
%feature("docstring") itk::simple::AddImageFilter "
577
Pixel-wise addition of two images.
580
This class is templated over the types of the two input images and the
581
type of the output image. Numeric conversions (castings) are done by
584
The pixel type of the input 1 image must have a valid definition of
585
the operator+ with a pixel type of the image 2. This condition is
586
required because internally this filter will perform the operation
589
Additionally the type resulting from the sum, will be cast to the
590
pixel type of the output image.
592
The total operation over one pixel will be
594
For example, this filter could be used directly for adding images
595
whose pixels are vectors of the same dimension, and to store the
596
resulting vector in an output image of vector pixels.
598
The images to be added are set using the methods:
600
Additionally, this filter can be used to add a constant to every pixel
605
No numeric overflow checking is performed in this filter.
610
Add two images together
612
Add a constant to every pixel in an image
614
itk::simple::Add for the procedural interface
616
itk::AddImageFilter for the Doxygen on the original ITK class.
620
C++ includes: sitkAddImageFilter.h
623
%feature("docstring") itk::simple::AddImageFilter::AddImageFilter "
625
Default Constructor that takes no arguments and initializes default
630
%feature("docstring") itk::simple::AddImageFilter::Execute "
632
Execute the filter on the input images
636
%feature("docstring") itk::simple::AddImageFilter::Execute "
638
Execute the filter with an image and a constant
642
%feature("docstring") itk::simple::AddImageFilter::Execute "
645
%feature("docstring") itk::simple::AddImageFilter::GetName "
651
%feature("docstring") itk::simple::AddImageFilter::ToString "
657
%feature("docstring") itk::simple::AddImageFilter::~AddImageFilter "
664
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter "
666
Alter an image with additive Gaussian white noise.
669
Additive Gaussian white noise can be modeled as:
674
where $ I $ is the observed image, $ I_0 $ is the noise-free image and $ N $ is a normally distributed random variable of mean $ \\\\mu $ and variance $ \\\\sigma^2 $ :
676
$ N \\\\sim \\\\mathcal{N}(\\\\mu, \\\\sigma^2) $
677
The noise is independent of the pixel intensities.
681
This code was contributed in the Insight Journal paper \"Noise
682
Simulation\". https://hdl.handle.net/10380/3158
684
itk::simple::AdditiveGaussianNoise for the procedural interface
686
itk::AdditiveGaussianNoiseImageFilter for the Doxygen on the original ITK class.
689
C++ includes: sitkAdditiveGaussianNoiseImageFilter.h
692
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::AdditiveGaussianNoiseImageFilter "
694
Default Constructor that takes no arguments and initializes default
699
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::Execute "
701
Execute the filter on the input image
705
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::Execute "
707
Execute the filter on the input image with the given parameters
711
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::GetMean "
713
Set/Get the mean of the Gaussian distribution. Defaults to 0.0.
717
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::GetName "
723
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::GetSeed "
726
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::GetStandardDeviation "
728
Set/Get the standard deviation of the Gaussian distribution. Defaults
733
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::SetMean "
735
Set/Get the mean of the Gaussian distribution. Defaults to 0.0.
739
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::SetSeed "
742
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::SetStandardDeviation "
744
Set/Get the standard deviation of the Gaussian distribution. Defaults
749
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::ToString "
755
%feature("docstring") itk::simple::AdditiveGaussianNoiseImageFilter::~AdditiveGaussianNoiseImageFilter "
762
%feature("docstring") itk::simple::AffineTransform "
764
An affine transformation about a fixed center with translation for a
773
C++ includes: sitkAffineTransform.h
776
%feature("docstring") itk::simple::AffineTransform::AffineTransform "
779
%feature("docstring") itk::simple::AffineTransform::AffineTransform "
782
%feature("docstring") itk::simple::AffineTransform::AffineTransform "
785
%feature("docstring") itk::simple::AffineTransform::AffineTransform "
788
%feature("docstring") itk::simple::AffineTransform::GetCenter "
791
%feature("docstring") itk::simple::AffineTransform::GetMatrix "
794
%feature("docstring") itk::simple::AffineTransform::GetName "
800
%feature("docstring") itk::simple::AffineTransform::GetTranslation "
806
%feature("docstring") itk::simple::AffineTransform::Rotate "
809
%feature("docstring") itk::simple::AffineTransform::Scale "
815
%feature("docstring") itk::simple::AffineTransform::Scale "
818
%feature("docstring") itk::simple::AffineTransform::SetCenter "
824
%feature("docstring") itk::simple::AffineTransform::SetMatrix "
827
%feature("docstring") itk::simple::AffineTransform::SetTranslation "
830
%feature("docstring") itk::simple::AffineTransform::Shear "
833
%feature("docstring") itk::simple::AffineTransform::Translate "
837
%feature("docstring") itk::simple::AggregateLabelMapFilter "
839
Collapses all labels into the first label.
842
This filter takes a label map as input and visits the pixels of all
843
labels and assigns them to the first label of the label map. At the
844
end of the execution of this filter, the map will contain a single
847
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
850
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
851
de Jouy-en-Josas, France.
854
ShapeLabelObject , RelabelComponentImageFilter
856
itk::simple::AggregateLabelMapFilter for the procedural interface
858
itk::AggregateLabelMapFilter for the Doxygen on the original ITK class.
861
C++ includes: sitkAggregateLabelMapFilter.h
864
%feature("docstring") itk::simple::AggregateLabelMapFilter::AggregateLabelMapFilter "
866
Default Constructor that takes no arguments and initializes default
871
%feature("docstring") itk::simple::AggregateLabelMapFilter::Execute "
873
Execute the filter on the input image
877
%feature("docstring") itk::simple::AggregateLabelMapFilter::GetName "
883
%feature("docstring") itk::simple::AggregateLabelMapFilter::ToString "
889
%feature("docstring") itk::simple::AggregateLabelMapFilter::~AggregateLabelMapFilter "
896
%feature("docstring") itk::simple::AndImageFilter "
898
Implements the AND bitwise operator pixel-wise between two images.
901
This class is templated over the types of the two input images and the
902
type of the output image. Numeric conversions (castings) are done by
905
Since the bitwise AND operation is only defined in C++ for integer
906
types, the images passed to this filter must comply with the
907
requirement of using integer pixel type.
909
The total operation over one pixel will be Where \"&\" is the bitwise AND operator in C++.
915
Binary AND two images
917
itk::simple::And for the procedural interface
919
itk::AndImageFilter for the Doxygen on the original ITK class.
923
C++ includes: sitkAndImageFilter.h
926
%feature("docstring") itk::simple::AndImageFilter::AndImageFilter "
928
Default Constructor that takes no arguments and initializes default
933
%feature("docstring") itk::simple::AndImageFilter::Execute "
935
Execute the filter on the input images
939
%feature("docstring") itk::simple::AndImageFilter::Execute "
941
Execute the filter with an image and a constant
945
%feature("docstring") itk::simple::AndImageFilter::Execute "
948
%feature("docstring") itk::simple::AndImageFilter::GetName "
954
%feature("docstring") itk::simple::AndImageFilter::ToString "
960
%feature("docstring") itk::simple::AndImageFilter::~AndImageFilter "
967
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter "
969
A method for estimation of a surface from a binary volume.
973
This filter implements a surface-fitting method for estimation of a
974
surface from a binary volume. This process can be used to reduce
975
aliasing artifacts which result in visualization of binary partitioned
978
The binary volume (filter input) is used as a set of constraints in an
979
iterative relaxation process of an estimated ND surface. The surface
980
is described implicitly as the zero level set of a volume $ \\\\phi $ and allowed to deform under curvature flow. A set of constraints is
981
imposed on this movement as follows:
983
\\\\[ u_{i,j,k}^{n+1} = \\\\left\\\\{ \\\\begin{array}{ll}
984
\\\\mbox{max} (u_{i,j,k}^{n} + \\\\Delta t H_{i,j,k}^{n}, 0) &
985
\\\\mbox{\\\\f$B_{i,j,k} = 1\\\\f$} \\\\\\\\ \\\\mbox{min}
986
(u_{i,j,k}^{n} + \\\\Delta t H_{i,j,k}^{n}, 0) &
987
\\\\mbox{\\\\f$B_{i,j,k} = -1\\\\f$} \\\\end{array}\\\\right. \\\\]
989
where $ u_{i,j,k}^{n} $ is the value of $ \\\\phi $ at discrete index $ (i,j,k) $ and iteration $ n $ , $ H $ is the gradient magnitude times mean curvature of $ \\\\phi $ , and $ B $ is the binary input volume, with 1 denoting an inside pixel and -1
990
denoting an outside pixel.
992
This implementation uses a sparse field level set solver instead of
993
the narrow band implementation described in the reference below, which
994
may introduce some differences in how fast and how accurately (in
995
terms of RMS error) the solution converges.
997
Whitaker, Ross. \"Reducing Aliasing Artifacts In Iso-Surfaces of
998
Binary Volumes\" IEEE Volume Visualization and Graphics Symposium,
999
October 2000, pp.23-32.
1001
The MaximumRMSChange parameter is used to determine when the solution
1002
has converged. A lower value will result in a tighter-fitting
1003
solution, but will require more computations. Too low a value could
1004
put the solver into an infinite loop. Values should always be less
1005
than 1.0. A value of 0.07 is a good starting estimate.
1007
The MaximumIterations parameter can be used to halt the solution after
1008
a specified number of iterations.
1010
The input is an N-dimensional image of any type. It is assumed to be a
1011
binary image. The filter will use an isosurface value that is halfway
1012
between the min and max values in the image. A signed data type is not
1013
necessary for the input.
1015
The filter will output a level set image of real, signed values. The
1016
zero crossings of this (N-dimensional) image represent the position of
1017
the isosurface value of interest. Values outside the zero level set
1018
are negative and values inside the zero level set are positive values.
1020
The output image type you use to instantiate this filter should be a
1021
real valued scalar type. In other words: doubles or floats.
1023
The filter is relatively straightforward to use. Tests and examples
1024
exist to illustrate. The important thing is to understand the input
1025
and output types so you can properly interperet your results.
1027
In the common case, the only parameter that will need to be set is the
1028
MaximumRMSChange parameter, which determines when the solver halts.
1033
Anti alias a binary image
1035
itk::simple::AntiAliasBinary for the procedural interface
1037
itk::AntiAliasBinaryImageFilter for the Doxygen on the original ITK class.
1041
C++ includes: sitkAntiAliasBinaryImageFilter.h
1044
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::AntiAliasBinaryImageFilter "
1046
Default Constructor that takes no arguments and initializes default
1051
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::Execute "
1053
Execute the filter on the input image
1057
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::Execute "
1059
Execute the filter on the input image with the given parameters
1063
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::GetElapsedIterations "
1065
Number of iterations run.
1068
This is a measurement. Its value is updated in the Execute methods, so
1069
the value will only be valid after an execution.
1073
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::GetMaximumRMSError "
1076
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::GetName "
1082
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::GetNumberOfIterations "
1085
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::GetRMSChange "
1087
The Root Mean Square of the levelset upon termination.
1090
This is a measurement. Its value is updated in the Execute methods, so
1091
the value will only be valid after an execution.
1095
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::SetMaximumRMSError "
1098
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::SetNumberOfIterations "
1101
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::ToString "
1107
%feature("docstring") itk::simple::AntiAliasBinaryImageFilter::~AntiAliasBinaryImageFilter "
1114
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter "
1116
Create a map of the approximate signed distance from the boundaries of
1120
The ApproximateSignedDistanceMapImageFilter takes as input a binary image and produces a signed distance map.
1121
Each pixel value in the output contains the approximate distance from
1122
that pixel to the nearest \"object\" in the binary image. This filter
1123
differs from the DanielssonDistanceMapImageFilter in that it calculates the distance to the \"object edge\" for pixels
1126
Negative values in the output indicate that the pixel at that position
1127
is within an object in the input image. The absolute value of a
1128
negative pixel represents the approximate distance to the nearest
1129
object boundary pixel.
1131
WARNING: This filter requires that the output type be floating-point.
1132
Otherwise internal calculations will not be performed to the
1133
appropriate precision, resulting in completely incorrect (read: zero-
1136
The distances computed by this filter are Chamfer distances, which are
1137
only an approximation to Euclidian distances, and are not as exact
1138
approximations as those calculated by the DanielssonDistanceMapImageFilter . On the other hand, this filter is faster.
1140
This filter requires that an \"inside value\" and \"outside value\" be
1141
set as parameters. The \"inside value\" is the intensity value of the
1142
binary image which corresponds to objects, and the \"outside value\"
1143
is the intensity of the background. (A typical binary image often
1144
represents objects as black (0) and background as white (usually 255),
1145
or vice-versa.) Note that this filter is slightly faster if the inside
1146
value is less than the outside value. Otherwise an extra iteration
1147
through the image is required.
1149
This filter uses the FastChamferDistanceImageFilter and the IsoContourDistanceImageFilter internally to perform the distance calculations.
1153
DanielssonDistanceMapImageFilter
1155
SignedDanielssonDistanceMapImageFilter
1157
SignedMaurerDistanceMapImageFilter
1159
FastChamferDistanceImageFilter
1161
IsoContourDistanceImageFilter
1168
Compute a distance map from objects in a binary image
1170
itk::simple::ApproximateSignedDistanceMap for the procedural interface
1172
itk::ApproximateSignedDistanceMapImageFilter for the Doxygen on the original ITK class.
1176
C++ includes: sitkApproximateSignedDistanceMapImageFilter.h
1179
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::ApproximateSignedDistanceMapImageFilter "
1181
Default Constructor that takes no arguments and initializes default
1186
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::Execute "
1188
Execute the filter on the input image
1192
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::Execute "
1194
Execute the filter on the input image with the given parameters
1198
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::GetInsideValue "
1200
Set/Get intensity value representing the interior of objects in the
1205
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::GetName "
1211
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::GetOutsideValue "
1213
Set/Get intensity value representing non-objects in the mask.
1217
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::SetInsideValue "
1219
Set/Get intensity value representing the interior of objects in the
1224
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::SetOutsideValue "
1226
Set/Get intensity value representing non-objects in the mask.
1230
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::ToString "
1236
%feature("docstring") itk::simple::ApproximateSignedDistanceMapImageFilter::~ApproximateSignedDistanceMapImageFilter "
1243
%feature("docstring") itk::simple::AsinImageFilter "
1245
Computes the sine of each pixel.
1248
This filter is templated over the pixel type of the input image and
1249
the pixel type of the output image.
1251
The filter walks over all the pixels in the input image, and for each
1252
pixel does the following:
1255
cast the pixel value to double ,
1257
apply the std::asin() function to the double value,
1259
cast the double value resulting from std::asin() to the pixel type of
1262
store the casted value into the output image.
1263
The filter expects both images to have the same dimension (e.g. both
1264
2D, or both 3D, or both ND)
1266
itk::simple::Asin for the procedural interface
1268
itk::AsinImageFilter for the Doxygen on the original ITK class.
1271
C++ includes: sitkAsinImageFilter.h
1274
%feature("docstring") itk::simple::AsinImageFilter::AsinImageFilter "
1276
Default Constructor that takes no arguments and initializes default
1281
%feature("docstring") itk::simple::AsinImageFilter::Execute "
1283
Execute the filter on the input image
1287
%feature("docstring") itk::simple::AsinImageFilter::GetName "
1293
%feature("docstring") itk::simple::AsinImageFilter::ToString "
1299
%feature("docstring") itk::simple::AsinImageFilter::~AsinImageFilter "
1306
%feature("docstring") itk::simple::Atan2ImageFilter "
1308
Computes two argument inverse tangent.
1311
The first argument to the atan function is provided by a pixel in the
1312
first input image (SetInput1() ) and the corresponding pixel in the
1313
second input image (SetInput2() ) is used as the second argument.
1315
This class is templated over the types of the two input images and the
1316
type of the output image. Numeric conversions (castings) are done by
1319
Both pixel input types are cast to double in order to be used as
1320
parameters of std::atan2() . The resulting double value is cast to the
1327
Compute the arctangent of each pixel.
1329
itk::simple::Atan2 for the procedural interface
1331
itk::Atan2ImageFilter for the Doxygen on the original ITK class.
1335
C++ includes: sitkAtan2ImageFilter.h
1338
%feature("docstring") itk::simple::Atan2ImageFilter::Atan2ImageFilter "
1340
Default Constructor that takes no arguments and initializes default
1345
%feature("docstring") itk::simple::Atan2ImageFilter::Execute "
1347
Execute the filter on the input images
1351
%feature("docstring") itk::simple::Atan2ImageFilter::Execute "
1353
Execute the filter with an image and a constant
1357
%feature("docstring") itk::simple::Atan2ImageFilter::Execute "
1360
%feature("docstring") itk::simple::Atan2ImageFilter::GetName "
1366
%feature("docstring") itk::simple::Atan2ImageFilter::ToString "
1372
%feature("docstring") itk::simple::Atan2ImageFilter::~Atan2ImageFilter "
1379
%feature("docstring") itk::simple::AtanImageFilter "
1381
Computes the one-argument inverse tangent of each pixel.
1384
This filter is templated over the pixel type of the input image and
1385
the pixel type of the output image.
1387
The filter walks over all the pixels in the input image, and for each
1388
pixel does the following:
1391
cast the pixel value to double ,
1393
apply the std::atan() function to the double value,
1395
cast the double value resulting from std::atan() to the pixel type of
1398
store the cast value into the output image.
1400
itk::simple::Atan for the procedural interface
1402
itk::AtanImageFilter for the Doxygen on the original ITK class.
1406
C++ includes: sitkAtanImageFilter.h
1409
%feature("docstring") itk::simple::AtanImageFilter::AtanImageFilter "
1411
Default Constructor that takes no arguments and initializes default
1416
%feature("docstring") itk::simple::AtanImageFilter::Execute "
1418
Execute the filter on the input image
1422
%feature("docstring") itk::simple::AtanImageFilter::GetName "
1428
%feature("docstring") itk::simple::AtanImageFilter::ToString "
1434
%feature("docstring") itk::simple::AtanImageFilter::~AtanImageFilter "
1441
%feature("docstring") itk::simple::BSplineTransform "
1443
A deformable transform over a bounded spatial domain using a BSpline
1444
representation for a 2D or 3D coordinate space.
1449
itk::BSplineTransform
1452
C++ includes: sitkBSplineTransform.h
1455
%feature("docstring") itk::simple::BSplineTransform::BSplineTransform "
1458
%feature("docstring") itk::simple::BSplineTransform::BSplineTransform "
1461
%feature("docstring") itk::simple::BSplineTransform::BSplineTransform "
1464
%feature("docstring") itk::simple::BSplineTransform::GetCoefficientImages "
1466
Get a vector of the coefficient images representing the BSpline.
1469
A lazy shallow copy of the images from ITK are performed. If they are
1470
modified in SimpleITK a deep copy will occur. However, if the
1471
coefficients are modified in ITK, then no copy will occur and the
1472
images help by SimpleITK may change.
1476
%feature("docstring") itk::simple::BSplineTransform::GetName "
1482
%feature("docstring") itk::simple::BSplineTransform::GetOrder "
1485
%feature("docstring") itk::simple::BSplineTransform::GetTransformDomainDirection "
1488
%feature("docstring") itk::simple::BSplineTransform::GetTransformDomainMeshSize "
1491
%feature("docstring") itk::simple::BSplineTransform::GetTransformDomainOrigin "
1494
%feature("docstring") itk::simple::BSplineTransform::GetTransformDomainPhysicalDimensions "
1497
%feature("docstring") itk::simple::BSplineTransform::SetTransformDomainDirection "
1499
parameters fixed parameter
1503
%feature("docstring") itk::simple::BSplineTransform::SetTransformDomainMeshSize "
1506
%feature("docstring") itk::simple::BSplineTransform::SetTransformDomainOrigin "
1509
%feature("docstring") itk::simple::BSplineTransform::SetTransformDomainPhysicalDimensions "
1513
%feature("docstring") itk::simple::BSplineTransformInitializerFilter "
1515
BSplineTransformInitializerFilter is a helper class intended to initialize the control point grid such
1516
that it has a physically consistent definition. It sets the transform
1517
domain origin, physical dimensions and direction from information
1518
obtained from the image. It also sets the mesh size if asked to do so
1519
by calling SetTransformDomainMeshSize()before calling InitializeTransform().
1526
itk::simple::BSplineTransformInitializer for the procedural interface
1528
itk::BSplineTransformInitializer for the Doxygen on the original ITK class.
1531
C++ includes: sitkBSplineTransformInitializerFilter.h
1534
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::BSplineTransformInitializerFilter "
1536
Default Constructor that takes no arguments and initializes default
1541
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::Execute "
1543
Execute the filter on the input image
1547
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::Execute "
1549
Execute the filter on the input image with the given parameters
1553
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::GetName "
1559
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::GetOrder "
1562
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::GetTransformDomainMeshSize "
1565
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::SetOrder "
1567
The order of the bspline in the output BSplineTransform. This value effects the number of control points.
1571
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::SetTransformDomainMeshSize "
1573
Allow the user to set the mesh size of the transform via the
1574
initializer even though the initializer does not do anything with that
1575
information. Defeault = 1^ImageDimension.
1579
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::ToString "
1585
%feature("docstring") itk::simple::BSplineTransformInitializerFilter::~BSplineTransformInitializerFilter "
1592
%feature("docstring") itk::simple::BilateralImageFilter "
1594
Blurs an image while preserving edges.
1597
This filter uses bilateral filtering to blur an image using both
1598
domain and range \"neighborhoods\". Pixels that are close to a pixel
1599
in the image domain and similar to a pixel in the image range are used
1600
to calculate the filtered value. Two gaussian kernels (one in the
1601
image domain and one in the image range) are used to smooth the image.
1602
The result is an image that is smoothed in homogeneous regions yet has
1603
edges preserved. The result is similar to anisotropic diffusion but
1604
the implementation in non-iterative. Another benefit to bilateral
1605
filtering is that any distance metric can be used for kernel smoothing
1606
the image range. Hence, color images can be smoothed as vector images,
1607
using the CIE distances between intensity values as the similarity
1608
metric (the Gaussian kernel for the image domain is evaluated using
1609
CIE distances). A separate version of this filter will be designed for
1610
color and vector images.
1612
Bilateral filtering is capable of reducing the noise in an image by an
1613
order of magnitude while maintaining edges.
1615
The bilateral operator used here was described by Tomasi and Manduchi
1616
(Bilateral Filtering for Gray and ColorImages. IEEE ICCV. 1998.)
1622
RecursiveGaussianImageFilter
1624
DiscreteGaussianImageFilter
1626
AnisotropicDiffusionImageFilter
1632
NeighborhoodOperator
1633
TodoSupport color images
1635
Support vector images
1641
Bilateral filter an image
1643
itk::simple::Bilateral for the procedural interface
1645
itk::BilateralImageFilter for the Doxygen on the original ITK class.
1649
C++ includes: sitkBilateralImageFilter.h
1652
%feature("docstring") itk::simple::BilateralImageFilter::BilateralImageFilter "
1654
Default Constructor that takes no arguments and initializes default
1659
%feature("docstring") itk::simple::BilateralImageFilter::Execute "
1661
Execute the filter on the input image
1665
%feature("docstring") itk::simple::BilateralImageFilter::Execute "
1667
Execute the filter on the input image with the given parameters
1671
%feature("docstring") itk::simple::BilateralImageFilter::GetDomainSigma "
1673
Standard get/set macros for filter parameters. DomainSigma is
1674
specified in the same units as the Image spacing. RangeSigma is specified in the units of intensity.
1678
%feature("docstring") itk::simple::BilateralImageFilter::GetName "
1684
%feature("docstring") itk::simple::BilateralImageFilter::GetNumberOfRangeGaussianSamples "
1686
Set/Get the number of samples in the approximation to the Gaussian
1687
used for the range smoothing. Samples are only generated in the range
1688
of [0, 4*m_RangeSigma]. Default is 100.
1692
%feature("docstring") itk::simple::BilateralImageFilter::GetRangeSigma "
1694
Standard get/set macros for filter parameters. DomainSigma is
1695
specified in the same units as the Image spacing. RangeSigma is specified in the units of intensity.
1699
%feature("docstring") itk::simple::BilateralImageFilter::SetDomainSigma "
1701
Convenience get/set methods for setting all domain parameters to the
1706
%feature("docstring") itk::simple::BilateralImageFilter::SetNumberOfRangeGaussianSamples "
1708
Set/Get the number of samples in the approximation to the Gaussian
1709
used for the range smoothing. Samples are only generated in the range
1710
of [0, 4*m_RangeSigma]. Default is 100.
1714
%feature("docstring") itk::simple::BilateralImageFilter::SetRangeSigma "
1716
Standard get/set macros for filter parameters. DomainSigma is
1717
specified in the same units as the Image spacing. RangeSigma is specified in the units of intensity.
1721
%feature("docstring") itk::simple::BilateralImageFilter::ToString "
1727
%feature("docstring") itk::simple::BilateralImageFilter::~BilateralImageFilter "
1734
%feature("docstring") itk::simple::BinShrinkImageFilter "
1736
Reduce the size of an image by an integer factor in each dimension
1737
while performing averaging of an input neighborhood.
1740
The output image size in each dimension is given by:
1742
outputSize[j] = max( std::floor(inputSize[j]/shrinkFactor[j]), 1 );
1744
The algorithm implemented can be describe with the following equation
1745
for 2D: \\\\[ \\\\mathsf{I}_{out}(x_o,x_1) =
1746
\\\\frac{\\\\sum_{i=0}^{f_0}\\\\sum_{j=0}^{f_1}\\\\mathsf{I}_{in}(f_0
1747
x_o+i,f_1 x_1+j)}{f_0 f_1} \\\\]
1749
This filter is implemented so that the starting extent of the first
1750
pixel of the output matches that of the input.
1752
The change in image geometry from a 5x5 image binned by a factor of
1753
2x2. This code was contributed in the Insight Journal paper:
1754
\"BinShrink: A multi-resolution filter with cache efficient
1755
averaging\" by Lowekamp B., Chen D. https://hdl.handle.net/10380/3450
1757
itk::simple::BinShrink for the procedural interface
1759
itk::BinShrinkImageFilter for the Doxygen on the original ITK class.
1762
C++ includes: sitkBinShrinkImageFilter.h
1765
%feature("docstring") itk::simple::BinShrinkImageFilter::BinShrinkImageFilter "
1767
Default Constructor that takes no arguments and initializes default
1772
%feature("docstring") itk::simple::BinShrinkImageFilter::Execute "
1774
Execute the filter on the input image
1778
%feature("docstring") itk::simple::BinShrinkImageFilter::Execute "
1780
Execute the filter on the input image with the given parameters
1784
%feature("docstring") itk::simple::BinShrinkImageFilter::GetName "
1790
%feature("docstring") itk::simple::BinShrinkImageFilter::GetShrinkFactors "
1792
Get the shrink factors.
1796
%feature("docstring") itk::simple::BinShrinkImageFilter::SetShrinkFactor "
1798
Custom public declarations
1802
%feature("docstring") itk::simple::BinShrinkImageFilter::SetShrinkFactors "
1804
Set the shrink factors. Values are clamped to a minimum value of 1.
1805
Default is 1 for all dimensions.
1809
%feature("docstring") itk::simple::BinShrinkImageFilter::ToString "
1815
%feature("docstring") itk::simple::BinShrinkImageFilter::~BinShrinkImageFilter "
1822
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter "
1824
binary closing by reconstruction of an image.
1827
This filter removes small (i.e., smaller than the structuring element)
1828
holes in the image. It is defined as: Closing(f) =
1829
ReconstructionByErosion(Dilation(f)).
1831
The structuring element is assumed to be composed of binary values
1832
(zero or one). Only elements of the structuring element having values
1833
> 0 are candidates for affecting the center pixel.
1836
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
1837
de Jouy-en-Josas, France.
1838
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
1842
MorphologyImageFilter , ClosingByReconstructionImageFilter , BinaryOpeningByReconstructionImageFilter
1844
itk::simple::BinaryClosingByReconstruction for the procedural interface
1846
itk::BinaryClosingByReconstructionImageFilter for the Doxygen on the original ITK class.
1849
C++ includes: sitkBinaryClosingByReconstructionImageFilter.h
1852
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::BinaryClosingByReconstructionImageFilter "
1854
Default Constructor that takes no arguments and initializes default
1859
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::Execute "
1861
Execute the filter on the input image
1865
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::Execute "
1867
Execute the filter on the input image with the given parameters
1871
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::FullyConnectedOff "
1874
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::FullyConnectedOn "
1876
Set the value of FullyConnected to true or false respectfully.
1880
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::GetForegroundValue "
1882
Get the value in the image considered as \"foreground\". Defaults to
1883
maximum value of InputPixelType.
1887
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::GetFullyConnected "
1889
Set/Get whether the connected components are defined strictly by face
1890
connectivity or by face+edge+vertex connectivity. Default is
1891
FullyConnectedOff. For objects that are 1 pixel wide, use
1896
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::GetKernelRadius "
1899
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::GetKernelType "
1902
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::GetName "
1908
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetForegroundValue "
1910
Set the value in the image to consider as \"foreground\". Defaults to
1911
maximum value of InputPixelType.
1915
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetFullyConnected "
1917
Set/Get whether the connected components are defined strictly by face
1918
connectivity or by face+edge+vertex connectivity. Default is
1919
FullyConnectedOff. For objects that are 1 pixel wide, use
1924
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetKernelRadius "
1926
Kernel radius as a scale for isotropic structures
1930
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetKernelRadius "
1932
Set/Get the radius of the kernel structuring element as a vector.
1934
If the dimension of the image is greater then the length of r, then
1935
the radius will be padded. If it is less the r will be truncated.
1939
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetKernelType "
1941
Set/Get the kernel or structuring elemenent used for the morphology
1945
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::SetKernelType "
1948
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::ToString "
1954
%feature("docstring") itk::simple::BinaryClosingByReconstructionImageFilter::~BinaryClosingByReconstructionImageFilter "
1961
%feature("docstring") itk::simple::BinaryContourImageFilter "
1963
Labels the pixels on the border of the objects in a binary image.
1966
BinaryContourImageFilter takes a binary image as input, where the pixels in the objects are
1967
the pixels with a value equal to ForegroundValue. Only the pixels on
1968
the contours of the objects are kept. The pixels not on the border are
1969
changed to BackgroundValue.
1971
The connectivity can be changed to minimum or maximum connectivity
1972
with SetFullyConnected() . Full connectivity produces thicker contours.
1974
https://hdl.handle.net/1926/1352
1977
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
1978
de Jouy-en-Josas, France.
1981
LabelContourImageFilter BinaryErodeImageFilter SimpleContourExtractorImageFilter
1986
Extract the boundaries of connected regions in a binary image
1988
Extract the inner and outer boundaries of blobs in a binary image
1990
itk::simple::BinaryContour for the procedural interface
1992
itk::BinaryContourImageFilter for the Doxygen on the original ITK class.
1996
C++ includes: sitkBinaryContourImageFilter.h
1999
%feature("docstring") itk::simple::BinaryContourImageFilter::BinaryContourImageFilter "
2001
Default Constructor that takes no arguments and initializes default
2006
%feature("docstring") itk::simple::BinaryContourImageFilter::Execute "
2008
Execute the filter on the input image
2012
%feature("docstring") itk::simple::BinaryContourImageFilter::Execute "
2014
Execute the filter on the input image with the given parameters
2018
%feature("docstring") itk::simple::BinaryContourImageFilter::FullyConnectedOff "
2021
%feature("docstring") itk::simple::BinaryContourImageFilter::FullyConnectedOn "
2023
Set the value of FullyConnected to true or false respectfully.
2027
%feature("docstring") itk::simple::BinaryContourImageFilter::GetBackgroundValue "
2029
Set/Get the background value used to mark the pixels not on the border
2034
%feature("docstring") itk::simple::BinaryContourImageFilter::GetForegroundValue "
2036
Set/Get the foreground value used to identify the objects in the input
2041
%feature("docstring") itk::simple::BinaryContourImageFilter::GetFullyConnected "
2043
Set/Get whether the connected components are defined strictly by face
2044
connectivity or by face+edge+vertex connectivity. Default is
2045
FullyConnectedOff. For objects that are 1 pixel wide, use
2050
%feature("docstring") itk::simple::BinaryContourImageFilter::GetName "
2056
%feature("docstring") itk::simple::BinaryContourImageFilter::SetBackgroundValue "
2058
Set/Get the background value used to mark the pixels not on the border
2063
%feature("docstring") itk::simple::BinaryContourImageFilter::SetForegroundValue "
2065
Set/Get the foreground value used to identify the objects in the input
2070
%feature("docstring") itk::simple::BinaryContourImageFilter::SetFullyConnected "
2072
Set/Get whether the connected components are defined strictly by face
2073
connectivity or by face+edge+vertex connectivity. Default is
2074
FullyConnectedOff. For objects that are 1 pixel wide, use
2079
%feature("docstring") itk::simple::BinaryContourImageFilter::ToString "
2085
%feature("docstring") itk::simple::BinaryContourImageFilter::~BinaryContourImageFilter "
2092
%feature("docstring") itk::simple::BinaryDilateImageFilter "
2094
Fast binary dilation.
2097
BinaryDilateImageFilter is a binary dilation morphologic operation. This implementation is
2098
based on the papers:
2100
L.Vincent \"Morphological transformations of binary images with
2101
arbitrary structuring elements\", and
2103
N.Nikopoulos et al. \"An efficient algorithm for 3d binary
2104
morphological transformations with 3d structuring elements for
2105
arbitrary size and shape\". IEEE Transactions on Image Processing. Vol. 9. No. 3. 2000. pp. 283-286.
2107
Gray scale images can be processed as binary images by selecting a
2108
\"DilateValue\". Pixel values matching the dilate value are considered
2109
the \"foreground\" and all other pixels are \"background\". This is
2110
useful in processing segmented images where all pixels in segment #1
2111
have value 1 and pixels in segment #2 have value 2, etc. A particular
2112
\"segment number\" can be processed. DilateValue defaults to the
2113
maximum possible value of the PixelType.
2115
The structuring element is assumed to be composed of binary values
2116
(zero or one). Only elements of the structuring element having values
2117
> 0 are candidates for affecting the center pixel. A reasonable choice
2118
of structuring element is itk::BinaryBallStructuringElement .
2122
ImageToImageFilter BinaryErodeImageFilter BinaryMorphologyImageFilter
2127
Dilate a binary image
2129
itk::simple::BinaryDilate for the procedural interface
2131
itk::BinaryDilateImageFilter for the Doxygen on the original ITK class.
2135
C++ includes: sitkBinaryDilateImageFilter.h
2138
%feature("docstring") itk::simple::BinaryDilateImageFilter::BinaryDilateImageFilter "
2140
Default Constructor that takes no arguments and initializes default
2145
%feature("docstring") itk::simple::BinaryDilateImageFilter::BoundaryToForegroundOff "
2148
%feature("docstring") itk::simple::BinaryDilateImageFilter::BoundaryToForegroundOn "
2150
Set the value of BoundaryToForeground to true or false respectfully.
2154
%feature("docstring") itk::simple::BinaryDilateImageFilter::Execute "
2156
Execute the filter on the input image
2160
%feature("docstring") itk::simple::BinaryDilateImageFilter::Execute "
2162
Execute the filter on the input image with the given parameters
2166
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetBackgroundValue "
2169
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetBoundaryToForeground "
2172
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetForegroundValue "
2175
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetKernelRadius "
2178
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetKernelType "
2181
%feature("docstring") itk::simple::BinaryDilateImageFilter::GetName "
2187
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetBackgroundValue "
2190
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetBoundaryToForeground "
2193
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetForegroundValue "
2196
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetKernelRadius "
2198
Kernel radius as a scale for isotropic structures
2202
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetKernelRadius "
2204
Set/Get the radius of the kernel structuring element as a vector.
2206
If the dimension of the image is greater then the length of r, then
2207
the radius will be padded. If it is less the r will be truncated.
2211
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetKernelType "
2213
Set/Get the kernel or structuring elemenent used for the morphology
2217
%feature("docstring") itk::simple::BinaryDilateImageFilter::SetKernelType "
2220
%feature("docstring") itk::simple::BinaryDilateImageFilter::ToString "
2226
%feature("docstring") itk::simple::BinaryDilateImageFilter::~BinaryDilateImageFilter "
2233
%feature("docstring") itk::simple::BinaryErodeImageFilter "
2235
Fast binary erosion.
2238
BinaryErodeImageFilter is a binary erosion morphologic operation. This implementation is
2239
based on the papers:
2241
L.Vincent \"Morphological transformations of binary images with
2242
arbitrary structuring elements\", and
2244
N.Nikopoulos et al. \"An efficient algorithm for 3d binary
2245
morphological transformations with 3d structuring elements for
2246
arbitrary size and shape\". IEEE Transactions on Image Processing. Vol. 9. No. 3. 2000. pp. 283-286.
2248
Gray scale images can be processed as binary images by selecting a
2249
\"ErodeValue\". Pixel values matching the erode value are considered
2250
the \"foreground\" and all other pixels are \"background\". This is
2251
useful in processing segmented images where all pixels in segment #1
2252
have value 1 and pixels in segment #2 have value 2, etc. A particular
2253
\"segment number\" can be processed. ErodeValue defaults to the
2254
maximum possible value of the PixelType. The eroded pixels will
2255
receive the BackgroundValue (defaults to 0).
2257
The structuring element is assumed to be composed of binary values
2258
(zero or one). Only elements of the structuring element having values
2259
> 0 are candidates for affecting the center pixel. A reasonable choice
2260
of structuring element is itk::BinaryBallStructuringElement .
2264
ImageToImageFilter BinaryDilateImageFilter BinaryMorphologyImageFilter
2269
Erode a binary image
2271
itk::simple::BinaryErode for the procedural interface
2273
itk::BinaryErodeImageFilter for the Doxygen on the original ITK class.
2277
C++ includes: sitkBinaryErodeImageFilter.h
2280
%feature("docstring") itk::simple::BinaryErodeImageFilter::BinaryErodeImageFilter "
2282
Default Constructor that takes no arguments and initializes default
2287
%feature("docstring") itk::simple::BinaryErodeImageFilter::BoundaryToForegroundOff "
2290
%feature("docstring") itk::simple::BinaryErodeImageFilter::BoundaryToForegroundOn "
2292
Set the value of BoundaryToForeground to true or false respectfully.
2296
%feature("docstring") itk::simple::BinaryErodeImageFilter::Execute "
2298
Execute the filter on the input image
2302
%feature("docstring") itk::simple::BinaryErodeImageFilter::Execute "
2304
Execute the filter on the input image with the given parameters
2308
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetBackgroundValue "
2311
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetBoundaryToForeground "
2314
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetForegroundValue "
2317
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetKernelRadius "
2320
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetKernelType "
2323
%feature("docstring") itk::simple::BinaryErodeImageFilter::GetName "
2329
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetBackgroundValue "
2332
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetBoundaryToForeground "
2335
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetForegroundValue "
2338
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetKernelRadius "
2340
Kernel radius as a scale for isotropic structures
2344
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetKernelRadius "
2346
Set/Get the radius of the kernel structuring element as a vector.
2348
If the dimension of the image is greater then the length of r, then
2349
the radius will be padded. If it is less the r will be truncated.
2353
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetKernelType "
2355
Set/Get the kernel or structuring elemenent used for the morphology
2359
%feature("docstring") itk::simple::BinaryErodeImageFilter::SetKernelType "
2362
%feature("docstring") itk::simple::BinaryErodeImageFilter::ToString "
2368
%feature("docstring") itk::simple::BinaryErodeImageFilter::~BinaryErodeImageFilter "
2375
%feature("docstring") itk::simple::BinaryFillholeImageFilter "
2377
Remove holes not connected to the boundary of the image.
2380
BinaryFillholeImageFilter fills holes in a binary image.
2382
Geodesic morphology and the Fillhole algorithm is described in Chapter
2383
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
2384
and Applications\", Second Edition, Springer, 2003.
2387
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
2388
de Jouy-en-Josas, France.
2389
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
2393
GrayscaleFillholeImageFilter
2395
itk::simple::BinaryFillhole for the procedural interface
2397
itk::BinaryFillholeImageFilter for the Doxygen on the original ITK class.
2400
C++ includes: sitkBinaryFillholeImageFilter.h
2403
%feature("docstring") itk::simple::BinaryFillholeImageFilter::BinaryFillholeImageFilter "
2405
Default Constructor that takes no arguments and initializes default
2410
%feature("docstring") itk::simple::BinaryFillholeImageFilter::Execute "
2412
Execute the filter on the input image
2416
%feature("docstring") itk::simple::BinaryFillholeImageFilter::Execute "
2418
Execute the filter on the input image with the given parameters
2422
%feature("docstring") itk::simple::BinaryFillholeImageFilter::FullyConnectedOff "
2425
%feature("docstring") itk::simple::BinaryFillholeImageFilter::FullyConnectedOn "
2427
Set the value of FullyConnected to true or false respectfully.
2431
%feature("docstring") itk::simple::BinaryFillholeImageFilter::GetForegroundValue "
2433
Get the value in the image considered as \"foreground\". Defaults to
2434
maximum value of InputPixelType.
2438
%feature("docstring") itk::simple::BinaryFillholeImageFilter::GetFullyConnected "
2440
Set/Get whether the connected components are defined strictly by face
2441
connectivity or by face+edge+vertex connectivity. Default is
2442
FullyConnectedOff. For objects that are 1 pixel wide, use
2447
%feature("docstring") itk::simple::BinaryFillholeImageFilter::GetName "
2453
%feature("docstring") itk::simple::BinaryFillholeImageFilter::SetForegroundValue "
2455
Set the value in the image to consider as \"foreground\". Defaults to
2456
maximum value of InputPixelType.
2460
%feature("docstring") itk::simple::BinaryFillholeImageFilter::SetFullyConnected "
2462
Set/Get whether the connected components are defined strictly by face
2463
connectivity or by face+edge+vertex connectivity. Default is
2464
FullyConnectedOff. For objects that are 1 pixel wide, use
2469
%feature("docstring") itk::simple::BinaryFillholeImageFilter::ToString "
2475
%feature("docstring") itk::simple::BinaryFillholeImageFilter::~BinaryFillholeImageFilter "
2482
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter "
2484
Remove the objects not connected to the boundary of the image.
2487
BinaryGrindPeakImageFilter ginds peaks in a grayscale image.
2489
Geodesic morphology and the grind peak algorithm is described in
2490
Chapter 6 of Pierre Soille's book \"Morphological Image Analysis:
2491
Principles and Applications\", Second Edition, Springer, 2003.
2494
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
2495
de Jouy-en-Josas, France.
2496
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
2500
GrayscaleGrindPeakImageFilter
2502
itk::simple::BinaryGrindPeak for the procedural interface
2504
itk::BinaryGrindPeakImageFilter for the Doxygen on the original ITK class.
2507
C++ includes: sitkBinaryGrindPeakImageFilter.h
2510
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::BinaryGrindPeakImageFilter "
2512
Default Constructor that takes no arguments and initializes default
2517
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::Execute "
2519
Execute the filter on the input image
2523
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::Execute "
2525
Execute the filter on the input image with the given parameters
2529
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::FullyConnectedOff "
2532
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::FullyConnectedOn "
2534
Set the value of FullyConnected to true or false respectfully.
2538
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::GetBackgroundValue "
2540
Set the value in eroded part of the image. Defaults to zero
2544
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::GetForegroundValue "
2546
Get the value in the image considered as \"foreground\". Defaults to
2547
maximum value of InputPixelType.
2551
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::GetFullyConnected "
2553
Set/Get whether the connected components are defined strictly by face
2554
connectivity or by face+edge+vertex connectivity. Default is
2555
FullyConnectedOff. For objects that are 1 pixel wide, use
2560
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::GetName "
2566
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::SetBackgroundValue "
2568
Set the value in eroded part of the image. Defaults to zero
2572
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::SetForegroundValue "
2574
Set the value in the image to consider as \"foreground\". Defaults to
2575
maximum value of InputPixelType.
2579
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::SetFullyConnected "
2581
Set/Get whether the connected components are defined strictly by face
2582
connectivity or by face+edge+vertex connectivity. Default is
2583
FullyConnectedOff. For objects that are 1 pixel wide, use
2588
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::ToString "
2594
%feature("docstring") itk::simple::BinaryGrindPeakImageFilter::~BinaryGrindPeakImageFilter "
2601
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter "
2603
Label the connected components in a binary image and produce a
2604
collection of label objects.
2607
BinaryImageToLabelMapFilter labels the objects in a binary image. Each distinct object is
2608
assigned a unique label. The final object labels start with 1 and are
2609
consecutive. Objects that are reached earlier by a raster order scan
2612
The GetOutput() function of this class returns an itk::LabelMap .
2614
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
2617
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
2618
de Jouy-en-Josas, France.
2621
ConnectedComponentImageFilter , LabelImageToLabelMapFilter , LabelMap , LabelObject
2626
Label binary regions in an image
2628
itk::simple::BinaryImageToLabelMapFilter for the procedural interface
2630
itk::BinaryImageToLabelMapFilter for the Doxygen on the original ITK class.
2634
C++ includes: sitkBinaryImageToLabelMapFilter.h
2637
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::BinaryImageToLabelMapFilter "
2639
Default Constructor that takes no arguments and initializes default
2644
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::Execute "
2646
Execute the filter on the input image
2650
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::Execute "
2652
Execute the filter on the input image with the given parameters
2656
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::FullyConnectedOff "
2659
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::FullyConnectedOn "
2661
Set the value of FullyConnected to true or false respectfully.
2665
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::GetFullyConnected "
2667
Set/Get whether the connected components are defined strictly by face
2668
connectivity or by face+edge+vertex connectivity. Default is
2669
FullyConnectedOff. For objects that are 1 pixel wide, use
2674
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::GetInputForegroundValue "
2676
Set/Get the value to be consider \"foreground\" in the input image.
2677
Defaults to NumericTraits<InputPixelType>::max() .
2681
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::GetName "
2687
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::GetOutputBackgroundValue "
2689
Set/Get the value used as \"background\" in the output image. Defaults
2690
to NumericTraits<OutputPixelType>::NonpositiveMin() .
2694
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::SetFullyConnected "
2696
Set/Get whether the connected components are defined strictly by face
2697
connectivity or by face+edge+vertex connectivity. Default is
2698
FullyConnectedOff. For objects that are 1 pixel wide, use
2703
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::SetInputForegroundValue "
2705
Set/Get the value to be consider \"foreground\" in the input image.
2706
Defaults to NumericTraits<InputPixelType>::max() .
2710
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::SetOutputBackgroundValue "
2712
Set/Get the value used as \"background\" in the output image. Defaults
2713
to NumericTraits<OutputPixelType>::NonpositiveMin() .
2717
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::ToString "
2723
%feature("docstring") itk::simple::BinaryImageToLabelMapFilter::~BinaryImageToLabelMapFilter "
2730
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter "
2732
Computes the square root of the sum of squares of corresponding input
2736
This filter is templated over the types of the two input images and
2737
the type of the output image.
2739
Numeric conversions (castings) are done by the C++ defaults.
2741
The filter walks over all of the pixels in the two input images, and
2742
for each pixel does the following:
2745
cast the input 1 pixel value to double
2747
cast the input 2 pixel value to double
2749
compute the sum of squares of the two pixel values
2751
compute the square root of the sum
2753
cast the double value resulting from std::sqrt() to the pixel type of
2756
store the cast value into the output image.
2757
The filter expects all images to have the same dimension (e.g. all
2758
2D, or all 3D, or all ND)
2760
itk::simple::BinaryMagnitude for the procedural interface
2762
itk::BinaryMagnitudeImageFilter for the Doxygen on the original ITK class.
2765
C++ includes: sitkBinaryMagnitudeImageFilter.h
2768
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter::BinaryMagnitudeImageFilter "
2770
Default Constructor that takes no arguments and initializes default
2775
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter::Execute "
2777
Execute the filter on the input images
2781
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter::GetName "
2787
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter::ToString "
2793
%feature("docstring") itk::simple::BinaryMagnitudeImageFilter::~BinaryMagnitudeImageFilter "
2800
%feature("docstring") itk::simple::BinaryMedianImageFilter "
2802
Applies a version of the median filter optimized for binary images.
2805
This filter was contributed by Bjorn Hanch Sollie after identifying
2806
that the generic Median filter performed unnecessary operations when
2807
the input image is binary.
2809
This filter computes an image where a given pixel is the median value
2810
of the pixels in a neighborhood about the corresponding input pixel.
2811
For the case of binary images the median can be obtained by simply
2812
counting the neighbors that are foreground.
2814
A median filter is one of the family of nonlinear filters. It is used
2815
to smooth an image without being biased by outliers or shot noise.
2823
NeighborhoodOperator
2825
NeighborhoodIterator
2827
itk::simple::BinaryMedian for the procedural interface
2829
itk::BinaryMedianImageFilter for the Doxygen on the original ITK class.
2832
C++ includes: sitkBinaryMedianImageFilter.h
2835
%feature("docstring") itk::simple::BinaryMedianImageFilter::BinaryMedianImageFilter "
2837
Default Constructor that takes no arguments and initializes default
2842
%feature("docstring") itk::simple::BinaryMedianImageFilter::Execute "
2844
Execute the filter on the input image
2848
%feature("docstring") itk::simple::BinaryMedianImageFilter::Execute "
2850
Execute the filter on the input image with the given parameters
2854
%feature("docstring") itk::simple::BinaryMedianImageFilter::GetBackgroundValue "
2856
Get the value associated with the Foreground (or the object) on the
2857
binary input image and the Background .
2861
%feature("docstring") itk::simple::BinaryMedianImageFilter::GetForegroundValue "
2863
Get the value associated with the Foreground (or the object) on the
2864
binary input image and the Background .
2868
%feature("docstring") itk::simple::BinaryMedianImageFilter::GetName "
2874
%feature("docstring") itk::simple::BinaryMedianImageFilter::GetRadius "
2876
Get the radius of the neighborhood used to compute the median
2880
%feature("docstring") itk::simple::BinaryMedianImageFilter::SetBackgroundValue "
2882
Set the value associated with the Foreground (or the object) on the
2883
binary input image and the Background .
2887
%feature("docstring") itk::simple::BinaryMedianImageFilter::SetForegroundValue "
2889
Set the value associated with the Foreground (or the object) on the
2890
binary input image and the Background .
2894
%feature("docstring") itk::simple::BinaryMedianImageFilter::SetRadius "
2896
Set the radius of the neighborhood used to compute the median.
2900
%feature("docstring") itk::simple::BinaryMedianImageFilter::SetRadius "
2902
Set the values of the Radius vector all to value
2906
%feature("docstring") itk::simple::BinaryMedianImageFilter::ToString "
2912
%feature("docstring") itk::simple::BinaryMedianImageFilter::~BinaryMedianImageFilter "
2919
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter "
2921
Denoise a binary image using min/max curvature flow.
2924
BinaryMinMaxCurvatureFlowImageFilter implements a curvature driven image denosing algorithm. This filter
2925
assumes that the image is essentially binary: consisting of two
2926
classes. Iso-brightness contours in the input image are viewed as a
2927
level set. The level set is then evolved using a curvature-based speed
2930
\\\\[ I_t = F_{\\\\mbox{minmax}} |\\\\nabla I| \\\\]
2932
where $ F_{\\\\mbox{minmax}} = \\\\min(\\\\kappa,0) $ if $ \\\\mbox{Avg}_{\\\\mbox{stencil}}(x) $ is less than or equal to $ T_{thresold} $ and $ \\\\max(\\\\kappa,0) $ , otherwise. $ \\\\kappa $ is the mean curvature of the iso-brightness contour at point $ x $ .
2934
In min/max curvature flow, movement is turned on or off depending on
2935
the scale of the noise one wants to remove. Switching depends on the
2936
average image value of a region of radius $ R $ around each point. The choice of $ R $ , the stencil radius, governs the scale of the noise to be removed.
2938
The threshold value $ T_{threshold} $ is a user specified value which discriminates between the two pixel
2941
This filter make use of the multi-threaded finite difference solver
2942
hierarchy. Updates are computed using a BinaryMinMaxCurvatureFlowFunction object. A zero flux Neumann boundary condition is used when computing
2943
derivatives near the data boundary.
2947
This filter assumes that the input and output types have the same
2948
dimensions. This filter also requires that the output image pixels are
2949
of a real type. This filter works for any dimensional images.
2950
Reference: \"Level Set Methods and Fast Marching Methods\", J.A.
2951
Sethian, Cambridge Press, Chapter 16, Second edition, 1999.
2955
BinaryMinMaxCurvatureFlowFunction
2957
CurvatureFlowImageFilter
2959
MinMaxCurvatureFlowImageFilter
2961
itk::simple::BinaryMinMaxCurvatureFlow for the procedural interface
2963
itk::BinaryMinMaxCurvatureFlowImageFilter for the Doxygen on the original ITK class.
2966
C++ includes: sitkBinaryMinMaxCurvatureFlowImageFilter.h
2969
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::BinaryMinMaxCurvatureFlowImageFilter "
2971
Default Constructor that takes no arguments and initializes default
2976
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::Execute "
2978
Execute the filter on the input image
2982
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::Execute "
2984
Execute the filter on the input image with the given parameters
2988
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::GetName "
2994
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::GetNumberOfIterations "
2997
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::GetStencilRadius "
3000
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::GetThreshold "
3002
Set/Get the threshold value.
3006
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::GetTimeStep "
3009
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::SetNumberOfIterations "
3012
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::SetStencilRadius "
3015
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::SetThreshold "
3017
Set/Get the threshold value.
3021
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::SetTimeStep "
3024
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::ToString "
3030
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlowImageFilter::~BinaryMinMaxCurvatureFlowImageFilter "
3037
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter "
3039
binary morphological closing of an image.
3042
This filter removes small (i.e., smaller than the structuring element)
3043
holes and tube like structures in the interior or at the boundaries of
3044
the image. The morphological closing of an image \"f\" is defined as:
3045
Closing(f) = Erosion(Dilation(f)).
3047
The structuring element is assumed to be composed of binary values
3048
(zero or one). Only elements of the structuring element having values
3049
> 0 are candidates for affecting the center pixel.
3051
This code was contributed in the Insight Journal paper: \"Binary
3052
morphological closing and opening image filters\" by Lehmann G. https://hdl.handle.net/1926/141 http://www.insight-journal.org/browse/publication/58
3055
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3056
de Jouy-en-Josas, France.
3059
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleErodeImageFilter
3061
itk::simple::BinaryMorphologicalClosing for the procedural interface
3063
itk::BinaryMorphologicalClosingImageFilter for the Doxygen on the original ITK class.
3066
C++ includes: sitkBinaryMorphologicalClosingImageFilter.h
3069
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::BinaryMorphologicalClosingImageFilter "
3071
Default Constructor that takes no arguments and initializes default
3076
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::Execute "
3078
Execute the filter on the input image
3082
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::Execute "
3084
Execute the filter on the input image with the given parameters
3088
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::GetForegroundValue "
3090
Get the value in the image considered as \"foreground\". Defaults to
3091
maximum value of InputPixelType.
3095
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::GetKernelRadius "
3098
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::GetKernelType "
3101
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::GetName "
3107
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::GetSafeBorder "
3109
A safe border is added to input image to avoid borders effects and
3110
remove it once the closing is done
3114
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SafeBorderOff "
3117
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SafeBorderOn "
3119
Set the value of SafeBorder to true or false respectfully.
3123
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetForegroundValue "
3125
Set the value in the image to consider as \"foreground\". Defaults to
3126
maximum value of InputPixelType.
3130
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetKernelRadius "
3132
Kernel radius as a scale for isotropic structures
3136
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetKernelRadius "
3138
Set/Get the radius of the kernel structuring element as a vector.
3140
If the dimension of the image is greater then the length of r, then
3141
the radius will be padded. If it is less the r will be truncated.
3145
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetKernelType "
3147
Set/Get the kernel or structuring elemenent used for the morphology
3151
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetKernelType "
3154
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::SetSafeBorder "
3156
A safe border is added to input image to avoid borders effects and
3157
remove it once the closing is done
3161
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::ToString "
3167
%feature("docstring") itk::simple::BinaryMorphologicalClosingImageFilter::~BinaryMorphologicalClosingImageFilter "
3174
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter "
3176
binary morphological opening of an image.
3179
This filter removes small (i.e., smaller than the structuring element)
3180
structures in the interior or at the boundaries of the image. The
3181
morphological opening of an image \"f\" is defined as: Opening(f) =
3182
Dilatation(Erosion(f)).
3184
The structuring element is assumed to be composed of binary values
3185
(zero or one). Only elements of the structuring element having values
3186
> 0 are candidates for affecting the center pixel.
3188
This code was contributed in the Insight Journal paper: \"Binary
3189
morphological closing and opening image filters\" by Lehmann G. https://hdl.handle.net/1926/141 http://www.insight-journal.org/browse/publication/58
3192
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3193
de Jouy-en-Josas, France.
3196
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleErodeImageFilter
3198
itk::simple::BinaryMorphologicalOpening for the procedural interface
3200
itk::BinaryMorphologicalOpeningImageFilter for the Doxygen on the original ITK class.
3203
C++ includes: sitkBinaryMorphologicalOpeningImageFilter.h
3206
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::BinaryMorphologicalOpeningImageFilter "
3208
Default Constructor that takes no arguments and initializes default
3213
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::Execute "
3215
Execute the filter on the input image
3219
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::Execute "
3221
Execute the filter on the input image with the given parameters
3225
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::GetBackgroundValue "
3227
Set the value in eroded part of the image. Defaults to zero
3231
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::GetForegroundValue "
3233
Get the value in the image considered as \"foreground\". Defaults to
3234
maximum value of PixelType.
3238
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::GetKernelRadius "
3241
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::GetKernelType "
3244
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::GetName "
3250
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetBackgroundValue "
3252
Set the value in eroded part of the image. Defaults to zero
3256
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetForegroundValue "
3258
Set the value in the image to consider as \"foreground\". Defaults to
3259
maximum value of PixelType.
3263
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetKernelRadius "
3265
Kernel radius as a scale for isotropic structures
3269
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetKernelRadius "
3271
Set/Get the radius of the kernel structuring element as a vector.
3273
If the dimension of the image is greater then the length of r, then
3274
the radius will be padded. If it is less the r will be truncated.
3278
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetKernelType "
3280
Set/Get the kernel or structuring elemenent used for the morphology
3284
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::SetKernelType "
3287
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::ToString "
3293
%feature("docstring") itk::simple::BinaryMorphologicalOpeningImageFilter::~BinaryMorphologicalOpeningImageFilter "
3300
%feature("docstring") itk::simple::BinaryNotImageFilter "
3302
Implements the BinaryNot logical operator pixel-wise between two
3306
This class is parametrized over the types of the two input images and
3307
the type of the output image. Numeric conversions (castings) are done
3308
by the C++ defaults.
3310
The total operation over one pixel will be
3312
output_pixel = static_cast<PixelType>( input1_pixel != input2_pixel )
3314
Where \"!=\" is the equality operator in C++.
3317
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3318
de Jouy-en-Josas, France.
3319
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
3325
Invert an image using the Binary Not operation
3327
itk::simple::BinaryNot for the procedural interface
3329
itk::BinaryNotImageFilter for the Doxygen on the original ITK class.
3333
C++ includes: sitkBinaryNotImageFilter.h
3336
%feature("docstring") itk::simple::BinaryNotImageFilter::BinaryNotImageFilter "
3338
Default Constructor that takes no arguments and initializes default
3343
%feature("docstring") itk::simple::BinaryNotImageFilter::Execute "
3345
Execute the filter on the input image
3349
%feature("docstring") itk::simple::BinaryNotImageFilter::Execute "
3351
Execute the filter on the input image with the given parameters
3355
%feature("docstring") itk::simple::BinaryNotImageFilter::GetBackgroundValue "
3357
Get the value used as \"background\". Defaults to NumericTraits<PixelType>::NonpositiveMin() .
3361
%feature("docstring") itk::simple::BinaryNotImageFilter::GetForegroundValue "
3363
Set/Get the value in the image considered as \"foreground\". Defaults
3364
to maximum value of PixelType.
3368
%feature("docstring") itk::simple::BinaryNotImageFilter::GetName "
3374
%feature("docstring") itk::simple::BinaryNotImageFilter::SetBackgroundValue "
3376
Set the value used as \"background\". Defaults to NumericTraits<PixelType>::NonpositiveMin() .
3380
%feature("docstring") itk::simple::BinaryNotImageFilter::SetForegroundValue "
3382
Set/Get the value in the image considered as \"foreground\". Defaults
3383
to maximum value of PixelType.
3387
%feature("docstring") itk::simple::BinaryNotImageFilter::ToString "
3393
%feature("docstring") itk::simple::BinaryNotImageFilter::~BinaryNotImageFilter "
3400
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter "
3402
binary morphological closing of an image.
3405
This filter removes small (i.e., smaller than the structuring element)
3406
objects in the image. It is defined as: Opening(f) =
3407
ReconstructionByDilatation(Erosion(f)).
3409
The structuring element is assumed to be composed of binary values
3410
(zero or one). Only elements of the structuring element having values
3411
> 0 are candidates for affecting the center pixel.
3414
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3415
de Jouy-en-Josas, France.
3416
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
3420
MorphologyImageFilter , OpeningByReconstructionImageFilter , BinaryClosingByReconstructionImageFilter
3422
itk::simple::BinaryOpeningByReconstruction for the procedural interface
3424
itk::BinaryOpeningByReconstructionImageFilter for the Doxygen on the original ITK class.
3427
C++ includes: sitkBinaryOpeningByReconstructionImageFilter.h
3430
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::BinaryOpeningByReconstructionImageFilter "
3432
Default Constructor that takes no arguments and initializes default
3437
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::Execute "
3439
Execute the filter on the input image
3443
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::Execute "
3445
Execute the filter on the input image with the given parameters
3449
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::FullyConnectedOff "
3452
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::FullyConnectedOn "
3454
Set the value of FullyConnected to true or false respectfully.
3458
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetBackgroundValue "
3460
Set the value in eroded part of the image. Defaults to zero
3464
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetForegroundValue "
3466
Get the value in the image considered as \"foreground\". Defaults to
3467
maximum value of PixelType.
3471
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetFullyConnected "
3473
Set/Get whether the connected components are defined strictly by face
3474
connectivity or by face+edge+vertex connectivity. Default is
3475
FullyConnectedOff. For objects that are 1 pixel wide, use
3480
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetKernelRadius "
3483
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetKernelType "
3486
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::GetName "
3492
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetBackgroundValue "
3494
Set the value in eroded part of the image. Defaults to zero
3498
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetForegroundValue "
3500
Set the value in the image to consider as \"foreground\". Defaults to
3501
maximum value of PixelType.
3505
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetFullyConnected "
3507
Set/Get whether the connected components are defined strictly by face
3508
connectivity or by face+edge+vertex connectivity. Default is
3509
FullyConnectedOff. For objects that are 1 pixel wide, use
3514
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetKernelRadius "
3516
Kernel radius as a scale for isotropic structures
3520
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetKernelRadius "
3522
Set/Get the radius of the kernel structuring element as a vector.
3524
If the dimension of the image is greater then the length of r, then
3525
the radius will be padded. If it is less the r will be truncated.
3529
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetKernelType "
3531
Set/Get the kernel or structuring elemenent used for the morphology
3535
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::SetKernelType "
3538
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::ToString "
3544
%feature("docstring") itk::simple::BinaryOpeningByReconstructionImageFilter::~BinaryOpeningByReconstructionImageFilter "
3551
%feature("docstring") itk::simple::BinaryProjectionImageFilter "
3556
This class was contributed to the Insight Journal by Gaetan Lehmann.
3557
The original paper can be found at https://hdl.handle.net/1926/164
3560
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3561
de Jouy-en-Josas, France.
3564
ProjectionImageFilter
3566
MedianProjectionImageFilter
3568
MeanProjectionImageFilter
3570
MeanProjectionImageFilter
3572
MaximumProjectionImageFilter
3574
MinimumProjectionImageFilter
3576
StandardDeviationProjectionImageFilter
3578
SumProjectionImageFilter
3580
itk::simple::BinaryProjection for the procedural interface
3582
itk::BinaryProjectionImageFilter for the Doxygen on the original ITK class.
3585
C++ includes: sitkBinaryProjectionImageFilter.h
3588
%feature("docstring") itk::simple::BinaryProjectionImageFilter::BinaryProjectionImageFilter "
3590
Default Constructor that takes no arguments and initializes default
3595
%feature("docstring") itk::simple::BinaryProjectionImageFilter::Execute "
3597
Execute the filter on the input image
3601
%feature("docstring") itk::simple::BinaryProjectionImageFilter::Execute "
3603
Execute the filter on the input image with the given parameters
3607
%feature("docstring") itk::simple::BinaryProjectionImageFilter::GetBackgroundValue "
3609
Get the value used as \"background\". Any pixel value which is not
3610
DilateValue is considered background. BackgroundValue is used for
3611
defining boundary conditions. Defaults to NumericTraits<PixelType>::NonpositiveMin() .
3615
%feature("docstring") itk::simple::BinaryProjectionImageFilter::GetForegroundValue "
3617
Get the value in the image considered as \"foreground\". Defaults to
3618
maximum value of PixelType.
3622
%feature("docstring") itk::simple::BinaryProjectionImageFilter::GetName "
3628
%feature("docstring") itk::simple::BinaryProjectionImageFilter::GetProjectionDimension "
3631
%feature("docstring") itk::simple::BinaryProjectionImageFilter::SetBackgroundValue "
3633
Set the value used as \"background\". Any pixel value which is not
3634
DilateValue is considered background. BackgroundValue is used for
3635
defining boundary conditions. Defaults to NumericTraits<PixelType>::NonpositiveMin() .
3639
%feature("docstring") itk::simple::BinaryProjectionImageFilter::SetForegroundValue "
3641
Set the value in the image to consider as \"foreground\". Defaults to
3642
maximum value of PixelType. Subclasses may alias this to DilateValue
3647
%feature("docstring") itk::simple::BinaryProjectionImageFilter::SetProjectionDimension "
3650
%feature("docstring") itk::simple::BinaryProjectionImageFilter::ToString "
3656
%feature("docstring") itk::simple::BinaryProjectionImageFilter::~BinaryProjectionImageFilter "
3663
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter "
3665
binary reconstruction by dilation of an image
3668
Reconstruction by dilation operates on a \"marker\" image and a
3669
\"mask\" image, and is defined as the dilation of the marker image
3670
with respect to the mask image iterated until stability.
3672
Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
3673
book \"Morphological Image Analysis: Principles and Applications\",
3674
Second Edition, Springer, 2003.
3677
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3678
de Jouy-en-Josas, France.
3679
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
3683
MorphologyImageFilter , ReconstructionByDilationImageFilter , BinaryReconstructionByErosionImageFilter
3685
itk::simple::BinaryReconstructionByDilation for the procedural interface
3687
itk::BinaryReconstructionByDilationImageFilter for the Doxygen on the original ITK class.
3690
C++ includes: sitkBinaryReconstructionByDilationImageFilter.h
3693
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::BinaryReconstructionByDilationImageFilter "
3695
Default Constructor that takes no arguments and initializes default
3700
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::Execute "
3702
Execute the filter on the input images
3706
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::Execute "
3708
Execute the filter on the input images with the given parameters
3712
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::FullyConnectedOff "
3715
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::FullyConnectedOn "
3717
Set the value of FullyConnected to true or false respectfully.
3721
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::GetBackgroundValue "
3723
Set/Get the value used as \"background\" in the output image. Defaults
3724
to NumericTraits<PixelType>::NonpositiveMin() .
3728
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::GetForegroundValue "
3730
Set/Get the value used as \"foreground\" in the output image. Defaults
3731
to NumericTraits<PixelType>::max() .
3735
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::GetFullyConnected "
3737
Set/Get whether the connected components are defined strictly by face
3738
connectivity or by face+edge+vertex connectivity. Default is
3739
FullyConnectedOff. For objects that are 1 pixel wide, use
3744
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::GetName "
3750
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::SetBackgroundValue "
3752
Set/Get the value used as \"background\" in the output image. Defaults
3753
to NumericTraits<PixelType>::NonpositiveMin() .
3757
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::SetForegroundValue "
3759
Set/Get the value used as \"foreground\" in the output image. Defaults
3760
to NumericTraits<PixelType>::max() .
3764
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::SetFullyConnected "
3766
Set/Get whether the connected components are defined strictly by face
3767
connectivity or by face+edge+vertex connectivity. Default is
3768
FullyConnectedOff. For objects that are 1 pixel wide, use
3773
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::ToString "
3779
%feature("docstring") itk::simple::BinaryReconstructionByDilationImageFilter::~BinaryReconstructionByDilationImageFilter "
3786
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter "
3788
binary reconstruction by erosion of an image
3791
Reconstruction by erosion operates on a \"marker\" image and a
3792
\"mask\" image, and is defined as the erosion of the marker image with
3793
respect to the mask image iterated until stability.
3795
Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
3796
book \"Morphological Image Analysis: Principles and Applications\",
3797
Second Edition, Springer, 2003.
3800
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
3801
de Jouy-en-Josas, France.
3802
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
3806
MorphologyImageFilter , ReconstructionByErosionImageFilter , BinaryReconstructionByDilationImageFilter
3808
itk::simple::BinaryReconstructionByErosion for the procedural interface
3810
itk::BinaryReconstructionByErosionImageFilter for the Doxygen on the original ITK class.
3813
C++ includes: sitkBinaryReconstructionByErosionImageFilter.h
3816
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::BinaryReconstructionByErosionImageFilter "
3818
Default Constructor that takes no arguments and initializes default
3823
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::Execute "
3825
Execute the filter on the input images
3829
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::Execute "
3831
Execute the filter on the input images with the given parameters
3835
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::FullyConnectedOff "
3838
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::FullyConnectedOn "
3840
Set the value of FullyConnected to true or false respectfully.
3844
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::GetBackgroundValue "
3846
Set/Get the value used as \"background\" in the output image. Defaults
3847
to NumericTraits<PixelType>::NonpositiveMin() .
3851
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::GetForegroundValue "
3853
Set/Get the value used as \"foreground\" in the output image. Defaults
3854
to NumericTraits<PixelType>::max() .
3858
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::GetFullyConnected "
3860
Set/Get whether the connected components are defined strictly by face
3861
connectivity or by face+edge+vertex connectivity. Default is
3862
FullyConnectedOff. For objects that are 1 pixel wide, use
3867
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::GetName "
3873
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::SetBackgroundValue "
3875
Set/Get the value used as \"background\" in the output image. Defaults
3876
to NumericTraits<PixelType>::NonpositiveMin() .
3880
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::SetForegroundValue "
3882
Set/Get the value used as \"foreground\" in the output image. Defaults
3883
to NumericTraits<PixelType>::max() .
3887
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::SetFullyConnected "
3889
Set/Get whether the connected components are defined strictly by face
3890
connectivity or by face+edge+vertex connectivity. Default is
3891
FullyConnectedOff. For objects that are 1 pixel wide, use
3896
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::ToString "
3902
%feature("docstring") itk::simple::BinaryReconstructionByErosionImageFilter::~BinaryReconstructionByErosionImageFilter "
3909
%feature("docstring") itk::simple::BinaryThinningImageFilter "
3911
This filter computes one-pixel-wide edges of the input image.
3914
This class is parametrized over the type of the input image and the
3915
type of the output image.
3917
The input is assumed to be a binary image. If the foreground pixels of
3918
the input image do not have a value of 1, they are rescaled to 1
3919
internally to simplify the computation.
3921
The filter will produce a skeleton of the object. The output
3922
background values are 0, and the foreground values are 1.
3924
This filter is a sequential thinning algorithm and known to be
3925
computational time dependable on the image size. The algorithm
3926
corresponds with the 2D implementation described in:
3928
Rafael C. Gonzales and Richard E. Woods. Digital Image Processing. Addison Wesley, 491-494, (1993).
3930
To do: Make this filter ND.
3934
MorphologyImageFilter
3939
Skeletonize/thin an image
3941
itk::simple::BinaryThinning for the procedural interface
3943
itk::BinaryThinningImageFilter for the Doxygen on the original ITK class.
3947
C++ includes: sitkBinaryThinningImageFilter.h
3950
%feature("docstring") itk::simple::BinaryThinningImageFilter::BinaryThinningImageFilter "
3952
Default Constructor that takes no arguments and initializes default
3957
%feature("docstring") itk::simple::BinaryThinningImageFilter::Execute "
3959
Execute the filter on the input image
3963
%feature("docstring") itk::simple::BinaryThinningImageFilter::GetName "
3969
%feature("docstring") itk::simple::BinaryThinningImageFilter::ToString "
3975
%feature("docstring") itk::simple::BinaryThinningImageFilter::~BinaryThinningImageFilter "
3982
%feature("docstring") itk::simple::BinaryThresholdImageFilter "
3984
Binarize an input image by thresholding.
3987
This filter produces an output image whose pixels are either one of
3988
two values ( OutsideValue or InsideValue ), depending on whether the
3989
corresponding input image pixels lie between the two thresholds (
3990
LowerThreshold and UpperThreshold ). Values equal to either threshold
3991
is considered to be between the thresholds.
3993
More precisely \\\\[ Output(x_i) = \\\\begin{cases} InsideValue & \\\\text{if
3994
\\\\f$LowerThreshold \\\\leq x_i \\\\leq UpperThreshold\\\\f$}
3995
\\\\\\\\ OutsideValue & \\\\text{otherwise} \\\\end{cases} \\\\]
3997
This filter is templated over the input image type and the output
4000
The filter expect both images to have the same number of dimensions.
4002
The default values for LowerThreshold and UpperThreshold are:
4003
LowerThreshold = NumericTraits<TInput>::NonpositiveMin() ; UpperThreshold = NumericTraits<TInput>::max() ; Therefore, generally only one of these needs to be set, depending
4004
on whether the user wants to threshold above or below the desired
4013
itk::simple::BinaryThreshold for the procedural interface
4015
itk::BinaryThresholdImageFilter for the Doxygen on the original ITK class.
4019
C++ includes: sitkBinaryThresholdImageFilter.h
4022
%feature("docstring") itk::simple::BinaryThresholdImageFilter::BinaryThresholdImageFilter "
4024
Default Constructor that takes no arguments and initializes default
4029
%feature("docstring") itk::simple::BinaryThresholdImageFilter::Execute "
4031
Execute the filter on the input image
4035
%feature("docstring") itk::simple::BinaryThresholdImageFilter::Execute "
4037
Execute the filter on the input image with the given parameters
4041
%feature("docstring") itk::simple::BinaryThresholdImageFilter::GetInsideValue "
4043
Get the \"inside\" pixel value.
4047
%feature("docstring") itk::simple::BinaryThresholdImageFilter::GetLowerThreshold "
4050
%feature("docstring") itk::simple::BinaryThresholdImageFilter::GetName "
4056
%feature("docstring") itk::simple::BinaryThresholdImageFilter::GetOutsideValue "
4058
Get the \"outside\" pixel value.
4062
%feature("docstring") itk::simple::BinaryThresholdImageFilter::GetUpperThreshold "
4064
Get the threshold values.
4068
%feature("docstring") itk::simple::BinaryThresholdImageFilter::SetInsideValue "
4070
Set the \"inside\" pixel value. The default value NumericTraits<OutputPixelType>::max()
4074
%feature("docstring") itk::simple::BinaryThresholdImageFilter::SetLowerThreshold "
4077
%feature("docstring") itk::simple::BinaryThresholdImageFilter::SetOutsideValue "
4079
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::ZeroValue() .
4083
%feature("docstring") itk::simple::BinaryThresholdImageFilter::SetUpperThreshold "
4085
Set the thresholds. The default lower threshold is NumericTraits<InputPixelType>::NonpositiveMin() . The default upper threshold is NumericTraits<InputPixelType>::max . An execption is thrown if the lower threshold is greater than the
4090
%feature("docstring") itk::simple::BinaryThresholdImageFilter::ToString "
4096
%feature("docstring") itk::simple::BinaryThresholdImageFilter::~BinaryThresholdImageFilter "
4103
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter "
4105
BinaryThreshold projection.
4108
This class was contributed to the Insight Journal by Gaetan Lehmann.
4109
the original paper can be found at https://hdl.handle.net/1926/164
4112
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
4113
de Jouy-en-Josas, France.
4116
ProjectionImageFilter
4118
MedianProjectionImageFilter
4120
MeanProjectionImageFilter
4122
MeanProjectionImageFilter
4124
MaximumProjectionImageFilter
4126
MinimumProjectionImageFilter
4128
StandardDeviationProjectionImageFilter
4130
SumProjectionImageFilter
4132
itk::simple::BinaryThresholdProjection for the procedural interface
4134
itk::BinaryThresholdProjectionImageFilter for the Doxygen on the original ITK class.
4137
C++ includes: sitkBinaryThresholdProjectionImageFilter.h
4140
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::BinaryThresholdProjectionImageFilter "
4142
Default Constructor that takes no arguments and initializes default
4147
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::Execute "
4149
Execute the filter on the input image
4153
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::Execute "
4155
Execute the filter on the input image with the given parameters
4159
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::GetBackgroundValue "
4161
Set/Get the output value used as \"background\". Defaults to NumericTraits<PixelType>::NonpositiveMin() .
4165
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::GetForegroundValue "
4167
Set/Get the output value used as \"foreground\". Defaults to maximum
4172
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::GetName "
4178
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::GetProjectionDimension "
4181
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::GetThresholdValue "
4183
Set/Get the input value consider as \"threshold\". Defaults to NumericTraits<InputPixelType>::max()
4187
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::SetBackgroundValue "
4189
Set/Get the output value used as \"background\". Defaults to NumericTraits<PixelType>::NonpositiveMin() .
4193
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::SetForegroundValue "
4195
Set/Get the output value used as \"foreground\". Defaults to maximum
4200
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::SetProjectionDimension "
4203
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::SetThresholdValue "
4205
Set/Get the input value consider as \"threshold\". Defaults to NumericTraits<InputPixelType>::max()
4209
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::ToString "
4215
%feature("docstring") itk::simple::BinaryThresholdProjectionImageFilter::~BinaryThresholdProjectionImageFilter "
4222
%feature("docstring") itk::simple::BinomialBlurImageFilter "
4224
Performs a separable blur on each dimension of an image.
4227
The binomial blur consists of a nearest neighbor average along each
4228
image dimension. The net result after n-iterations approaches
4229
convultion with a gaussian.
4237
itk::simple::BinomialBlur for the procedural interface
4239
itk::BinomialBlurImageFilter for the Doxygen on the original ITK class.
4243
C++ includes: sitkBinomialBlurImageFilter.h
4246
%feature("docstring") itk::simple::BinomialBlurImageFilter::BinomialBlurImageFilter "
4248
Default Constructor that takes no arguments and initializes default
4253
%feature("docstring") itk::simple::BinomialBlurImageFilter::Execute "
4255
Execute the filter on the input image
4259
%feature("docstring") itk::simple::BinomialBlurImageFilter::Execute "
4261
Execute the filter on the input image with the given parameters
4265
%feature("docstring") itk::simple::BinomialBlurImageFilter::GetName "
4271
%feature("docstring") itk::simple::BinomialBlurImageFilter::GetRepetitions "
4273
Get and set the number of times to repeat the filter.
4277
%feature("docstring") itk::simple::BinomialBlurImageFilter::SetRepetitions "
4279
Get and set the number of times to repeat the filter.
4283
%feature("docstring") itk::simple::BinomialBlurImageFilter::ToString "
4289
%feature("docstring") itk::simple::BinomialBlurImageFilter::~BinomialBlurImageFilter "
4296
%feature("docstring") itk::simple::BitwiseNotImageFilter "
4298
Implements pixel-wise generic operation on one image.
4301
This class is parameterized over the type of the input image and the
4302
type of the output image. It is also parameterized by the operation to
4303
be applied, using a Functor style.
4305
UnaryFunctorImageFilter allows the output dimension of the filter to be larger than the input
4306
dimension. Thus subclasses of the UnaryFunctorImageFilter (like the CastImageFilter ) can be used to promote a 2D image to a 3D image, etc.
4310
BinaryFunctorImageFilter TernaryFunctorImageFilter
4315
Apply a custom operation to each pixel in an image
4317
itk::simple::BitwiseNot for the procedural interface
4319
itk::UnaryFunctorImageFilter for the Doxygen on the original ITK class.
4323
C++ includes: sitkBitwiseNotImageFilter.h
4326
%feature("docstring") itk::simple::BitwiseNotImageFilter::BitwiseNotImageFilter "
4328
Default Constructor that takes no arguments and initializes default
4333
%feature("docstring") itk::simple::BitwiseNotImageFilter::Execute "
4335
Execute the filter on the input image
4339
%feature("docstring") itk::simple::BitwiseNotImageFilter::GetName "
4345
%feature("docstring") itk::simple::BitwiseNotImageFilter::ToString "
4351
%feature("docstring") itk::simple::BitwiseNotImageFilter::~BitwiseNotImageFilter "
4358
%feature("docstring") itk::simple::BlackTopHatImageFilter "
4360
Black top hat extracts local minima that are smaller than the
4361
structuring element.
4364
Black top hat extracts local minima that are smaller than the
4365
structuring element. It subtracts the background from the input image.
4366
The output of the filter transforms the black valleys into white
4369
Top-hats are described in Chapter 4.5 of Pierre Soille's book
4370
\"Morphological Image Analysis: Principles and Applications\", Second
4371
Edition, Springer, 2003.
4374
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
4375
de Jouy-en-Josas, France.
4378
itk::simple::BlackTopHat for the procedural interface
4380
itk::BlackTopHatImageFilter for the Doxygen on the original ITK class.
4383
C++ includes: sitkBlackTopHatImageFilter.h
4386
%feature("docstring") itk::simple::BlackTopHatImageFilter::BlackTopHatImageFilter "
4388
Default Constructor that takes no arguments and initializes default
4393
%feature("docstring") itk::simple::BlackTopHatImageFilter::Execute "
4395
Execute the filter on the input image
4399
%feature("docstring") itk::simple::BlackTopHatImageFilter::Execute "
4401
Execute the filter on the input image with the given parameters
4405
%feature("docstring") itk::simple::BlackTopHatImageFilter::GetKernelRadius "
4408
%feature("docstring") itk::simple::BlackTopHatImageFilter::GetKernelType "
4411
%feature("docstring") itk::simple::BlackTopHatImageFilter::GetName "
4417
%feature("docstring") itk::simple::BlackTopHatImageFilter::GetSafeBorder "
4419
A safe border is added to input image to avoid borders effects and
4420
remove it once the closing is done
4424
%feature("docstring") itk::simple::BlackTopHatImageFilter::SafeBorderOff "
4427
%feature("docstring") itk::simple::BlackTopHatImageFilter::SafeBorderOn "
4429
Set the value of SafeBorder to true or false respectfully.
4433
%feature("docstring") itk::simple::BlackTopHatImageFilter::SetKernelRadius "
4435
Kernel radius as a scale for isotropic structures
4439
%feature("docstring") itk::simple::BlackTopHatImageFilter::SetKernelRadius "
4441
Set/Get the radius of the kernel structuring element as a vector.
4443
If the dimension of the image is greater then the length of r, then
4444
the radius will be padded. If it is less the r will be truncated.
4448
%feature("docstring") itk::simple::BlackTopHatImageFilter::SetKernelType "
4450
Set/Get the kernel or structuring elemenent used for the morphology
4454
%feature("docstring") itk::simple::BlackTopHatImageFilter::SetKernelType "
4457
%feature("docstring") itk::simple::BlackTopHatImageFilter::SetSafeBorder "
4459
A safe border is added to input image to avoid borders effects and
4460
remove it once the closing is done
4464
%feature("docstring") itk::simple::BlackTopHatImageFilter::ToString "
4470
%feature("docstring") itk::simple::BlackTopHatImageFilter::~BlackTopHatImageFilter "
4477
%feature("docstring") itk::simple::BoundedReciprocalImageFilter "
4479
Computes 1/(1+x) for each pixel in the image.
4482
The filter expect both the input and output images to have the same
4483
number of dimensions, and both of a scalar image type.
4485
itk::simple::BoundedReciprocal for the procedural interface
4487
itk::BoundedReciprocalImageFilter for the Doxygen on the original ITK class.
4490
C++ includes: sitkBoundedReciprocalImageFilter.h
4493
%feature("docstring") itk::simple::BoundedReciprocalImageFilter::BoundedReciprocalImageFilter "
4495
Default Constructor that takes no arguments and initializes default
4500
%feature("docstring") itk::simple::BoundedReciprocalImageFilter::Execute "
4502
Execute the filter on the input image
4506
%feature("docstring") itk::simple::BoundedReciprocalImageFilter::GetName "
4512
%feature("docstring") itk::simple::BoundedReciprocalImageFilter::ToString "
4518
%feature("docstring") itk::simple::BoundedReciprocalImageFilter::~BoundedReciprocalImageFilter "
4525
%feature("docstring") itk::simple::BoxMeanImageFilter "
4527
Implements a fast rectangular mean filter using the accumulator
4531
This code was contributed in the Insight Journal paper: \"Efficient
4532
implementation of kernel filtering\" by Beare R., Lehmann G https://hdl.handle.net/1926/555 http://www.insight-journal.org/browse/publication/160
4538
itk::simple::BoxMean for the procedural interface
4540
itk::BoxMeanImageFilter for the Doxygen on the original ITK class.
4543
C++ includes: sitkBoxMeanImageFilter.h
4546
%feature("docstring") itk::simple::BoxMeanImageFilter::BoxMeanImageFilter "
4548
Default Constructor that takes no arguments and initializes default
4553
%feature("docstring") itk::simple::BoxMeanImageFilter::Execute "
4555
Execute the filter on the input image
4559
%feature("docstring") itk::simple::BoxMeanImageFilter::Execute "
4561
Execute the filter on the input image with the given parameters
4565
%feature("docstring") itk::simple::BoxMeanImageFilter::GetName "
4571
%feature("docstring") itk::simple::BoxMeanImageFilter::GetRadius "
4574
%feature("docstring") itk::simple::BoxMeanImageFilter::SetRadius "
4577
%feature("docstring") itk::simple::BoxMeanImageFilter::SetRadius "
4579
Set the values of the Radius vector all to value
4583
%feature("docstring") itk::simple::BoxMeanImageFilter::ToString "
4589
%feature("docstring") itk::simple::BoxMeanImageFilter::~BoxMeanImageFilter "
4596
%feature("docstring") itk::simple::BoxSigmaImageFilter "
4598
Implements a fast rectangular sigma filter using the accumulator
4602
This code was contributed in the Insight Journal paper: \"Efficient
4603
implementation of kernel filtering\" by Beare R., Lehmann G https://hdl.handle.net/1926/555 http://www.insight-journal.org/browse/publication/160
4609
itk::simple::BoxSigma for the procedural interface
4611
itk::BoxSigmaImageFilter for the Doxygen on the original ITK class.
4614
C++ includes: sitkBoxSigmaImageFilter.h
4617
%feature("docstring") itk::simple::BoxSigmaImageFilter::BoxSigmaImageFilter "
4619
Default Constructor that takes no arguments and initializes default
4624
%feature("docstring") itk::simple::BoxSigmaImageFilter::Execute "
4626
Execute the filter on the input image
4630
%feature("docstring") itk::simple::BoxSigmaImageFilter::Execute "
4632
Execute the filter on the input image with the given parameters
4636
%feature("docstring") itk::simple::BoxSigmaImageFilter::GetName "
4642
%feature("docstring") itk::simple::BoxSigmaImageFilter::GetRadius "
4645
%feature("docstring") itk::simple::BoxSigmaImageFilter::SetRadius "
4648
%feature("docstring") itk::simple::BoxSigmaImageFilter::SetRadius "
4650
Set the values of the Radius vector all to value
4654
%feature("docstring") itk::simple::BoxSigmaImageFilter::ToString "
4660
%feature("docstring") itk::simple::BoxSigmaImageFilter::~BoxSigmaImageFilter "
4667
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter "
4669
This filter is an implementation of a Canny edge detector for scalar-
4673
Based on John Canny's paper \"A Computational Approach to Edge
4674
Detection\"(IEEE Transactions on Pattern Analysis and Machine
4675
Intelligence, Vol. PAMI-8, No.6, November 1986), there are four major
4676
steps used in the edge-detection scheme: (1) Smooth the input image
4677
with Gaussian filter. (2) Calculate the second directional derivatives
4678
of the smoothed image. (3) Non-Maximum Suppression: the zero-crossings
4679
of 2nd derivative are found, and the sign of third derivative is used
4680
to find the correct extrema. (4) The hysteresis thresholding is
4681
applied to the gradient magnitude (multiplied with zero-crossings) of
4682
the smoothed image to find and link edges.
4685
The input to this filter should be a scalar, real-valued Itk image of
4686
arbitrary dimension. The output should also be a scalar, real-value
4687
Itk image of the same dimensionality.
4689
There are four parameters for this filter that control the sub-filters
4690
used by the algorithm.
4692
Variance and Maximum error are used in the Gaussian smoothing of the
4693
input image. See itkDiscreteGaussianImageFilter for information on
4696
Threshold is the lowest allowed value in the output image. Its data
4697
type is the same as the data type of the output image. Any values
4698
below the Threshold level will be replaced with the OutsideValue
4699
parameter value, whose default is zero.
4700
TodoEdge-linking will be added when an itk connected component
4701
labeling algorithm is available.
4705
DiscreteGaussianImageFilter
4707
ZeroCrossingImageFilter
4709
ThresholdImageFilter
4711
itk::simple::CannyEdgeDetection for the procedural interface
4713
itk::CannyEdgeDetectionImageFilter for the Doxygen on the original ITK class.
4716
C++ includes: sitkCannyEdgeDetectionImageFilter.h
4719
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::CannyEdgeDetectionImageFilter "
4721
Default Constructor that takes no arguments and initializes default
4726
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::Execute "
4728
Execute the filter on the input image
4732
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::Execute "
4734
Execute the filter on the input image with the given parameters
4738
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::GetLowerThreshold "
4741
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::GetMaximumError "
4743
Set/Get the maximum error of the Gaussian smoothing kernel in each
4744
dimensional direction.
4748
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::GetName "
4754
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::GetUpperThreshold "
4757
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::GetVariance "
4759
Set/Get the variance of the Gaussian smoothing filter.
4763
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetLowerThreshold "
4766
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetMaximumError "
4768
Set/Get the MaximumError parameter used by the Gaussian smoothing
4769
filter in this algorithm
4773
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetMaximumError "
4775
Set the values of the MaximumError vector all to value
4779
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetUpperThreshold "
4781
Set the Threshold value for detected edges. TODO: Document in the
4782
ITKv4 migration guide that the SetThreshold member function was
4783
removed from the CannyEdgeDetectionImageFilter , and that both UpperThreshold and LowerThreshold need to be set. To
4784
get the same results as with the SetThreshold method change
4785
\"myfilter->SetThrehsold\" to \"myfilter->SetUpperThreshold\", and add
4786
\"myfilter->SetLowerThreshold(GetUpperThreshold()/2.0)\".
4790
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetVariance "
4792
Set/Get the variance of the Gaussian smoothing filter.
4796
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::SetVariance "
4798
Set the values of the Variance vector all to value
4802
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::ToString "
4808
%feature("docstring") itk::simple::CannyEdgeDetectionImageFilter::~CannyEdgeDetectionImageFilter "
4815
%feature("docstring") itk::simple::CastImageFilter "
4817
A hybrid cast image filter to convert images to other types of images.
4820
Several different ITK classes are implemented under the hood, to
4821
convert between different image types.
4825
itk::simple::Cast for the procedural interface
4828
C++ includes: sitkCastImageFilter.h
4831
%feature("docstring") itk::simple::CastImageFilter::CastImageFilter "
4833
Default Constructor that takes no arguments and initializes default
4838
%feature("docstring") itk::simple::CastImageFilter::Execute "
4841
%feature("docstring") itk::simple::CastImageFilter::GetName "
4847
%feature("docstring") itk::simple::CastImageFilter::GetOutputPixelType "
4850
%feature("docstring") itk::simple::CastImageFilter::SetOutputPixelType "
4852
Set/Get the output pixel type
4856
%feature("docstring") itk::simple::CastImageFilter::ToString "
4860
%feature("docstring") itk::simple::CenteredTransformInitializerFilter "
4862
CenteredTransformInitializerFilter is a helper class intended to initialize the center of rotation and
4863
the translation of Transforms having the center of rotation among
4867
This class is connected to the fixed image, moving image and transform
4868
involved in the registration. Two modes of operation are possible:
4874
In the first mode, the geometrical center of the moving image is
4875
passed as initial center of rotation to the transform and the vector
4876
from the center of the fixed image to the center of the moving image
4877
is passed as the initial translation. This mode basically assumes that
4878
the anatomical objects to be registered are centered in their
4879
respective images. Hence the best initial guess for the registration
4880
is the one that superimposes those two centers.
4882
In the second mode, the moments of gray level values are computed for
4883
both images. The center of mass of the moving image is then used as
4884
center of rotation. The vector between the two centers of mass is
4885
passes as the initial translation to the transform. This second
4886
approach assumes that the moments of the anatomical objects are
4887
similar for both images and hence the best initial guess for
4888
registration is to superimpose both mass centers. Note that this
4889
assumption will probably not hold in multi-modality registration. \\\\sa itk::CenteredTransformInitializer
4891
C++ includes: sitkCenteredTransformInitializerFilter.h
4894
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::CenteredTransformInitializerFilter "
4896
Default Constructor that takes no arguments and initializes default
4901
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::Execute "
4903
Execute the filter on the input image
4907
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::Execute "
4909
Execute the filter on the input image with the given parameters
4913
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::GeometryOn "
4915
Select between using the geometrical center of the images or using the
4916
center of mass given by the image intensities.
4920
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::GetName "
4926
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::GetOperationMode "
4929
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::MomentsOn "
4931
Select between using the geometrical center of the images or using the
4932
center of mass given by the image intensities.
4936
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::SetOperationMode "
4939
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::ToString "
4945
%feature("docstring") itk::simple::CenteredTransformInitializerFilter::~CenteredTransformInitializerFilter "
4952
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter "
4954
CenteredVersorTransformInitializerFilter is a helper class intended to initialize the center of rotation,
4955
versor, and translation of the VersorRigid3DTransform.
4958
This class derived from the CenteredTransformInitializerand uses it in
4959
a more constrained context. It always uses the Moments mode, and also
4960
takes advantage of the second order moments in order to initialize the
4961
Versorrepresenting rotation.
4965
itk::CenteredVersorTransformInitializer for the Doxygen on the original ITK class.
4968
C++ includes: sitkCenteredVersorTransformInitializerFilter.h
4971
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::CenteredVersorTransformInitializerFilter "
4973
Default Constructor that takes no arguments and initializes default
4978
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::ComputeRotationOff "
4981
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::ComputeRotationOn "
4983
Set the value of ComputeRotation to true or false respectfully.
4987
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::Execute "
4989
Execute the filter on the input image
4993
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::Execute "
4995
Execute the filter on the input image with the given parameters
4999
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::GetComputeRotation "
5001
Enable the use of the principal axes of each image to compute an
5002
initial rotation that will align them.
5006
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::GetName "
5012
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::SetComputeRotation "
5014
Enable the use of the principal axes of each image to compute an
5015
initial rotation that will align them.
5019
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::ToString "
5025
%feature("docstring") itk::simple::CenteredVersorTransformInitializerFilter::~CenteredVersorTransformInitializerFilter "
5032
%feature("docstring") itk::simple::ChangeLabelImageFilter "
5034
Change Sets of Labels.
5037
This filter produces an output image whose pixels are either copied
5038
from the input if they are not being changed or are rewritten based on
5039
the change parameters
5041
This filter is templated over the input image type and the output
5044
The filter expect both images to have the same number of dimensions.
5047
Tim Kelliher. GE Research, Niskayuna, NY.
5049
This work was supported by a grant from DARPA, executed by the U.S.
5050
Army Medical Research and Materiel Command/TATRC Assistance Agreement,
5051
Contract::W81XWH-05-2-0059.
5054
itk::simple::ChangeLabel for the procedural interface
5056
itk::ChangeLabelImageFilter for the Doxygen on the original ITK class.
5059
C++ includes: sitkChangeLabelImageFilter.h
5062
%feature("docstring") itk::simple::ChangeLabelImageFilter::ChangeLabelImageFilter "
5064
Default Constructor that takes no arguments and initializes default
5069
%feature("docstring") itk::simple::ChangeLabelImageFilter::Execute "
5071
Execute the filter on the input image
5075
%feature("docstring") itk::simple::ChangeLabelImageFilter::Execute "
5077
Execute the filter on the input image with the given parameters
5081
%feature("docstring") itk::simple::ChangeLabelImageFilter::GetChangeMap "
5084
%feature("docstring") itk::simple::ChangeLabelImageFilter::GetName "
5090
%feature("docstring") itk::simple::ChangeLabelImageFilter::SetChangeMap "
5092
Set the entire change map
5096
%feature("docstring") itk::simple::ChangeLabelImageFilter::ToString "
5102
%feature("docstring") itk::simple::ChangeLabelImageFilter::~ChangeLabelImageFilter "
5109
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter "
5111
Replace the label Ids of selected LabelObjects with new label Ids.
5114
This filter takes as input a label map and a list of pairs of Label
5115
Ids, to produce as output a new label map where the label Ids have
5116
been replaced according to the pairs in the list.
5118
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
5121
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
5122
de Jouy-en-Josas, France.
5125
ShapeLabelObject , RelabelComponentImageFilter
5127
itk::simple::ChangeLabelLabelMapFilter for the procedural interface
5129
itk::ChangeLabelLabelMapFilter for the Doxygen on the original ITK class.
5132
C++ includes: sitkChangeLabelLabelMapFilter.h
5135
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::ChangeLabelLabelMapFilter "
5137
Default Constructor that takes no arguments and initializes default
5142
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::Execute "
5144
Execute the filter on the input image
5148
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::Execute "
5150
Execute the filter on the input image with the given parameters
5154
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::GetChangeMap "
5157
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::GetName "
5163
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::SetChangeMap "
5166
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::ToString "
5172
%feature("docstring") itk::simple::ChangeLabelLabelMapFilter::~ChangeLabelLabelMapFilter "
5179
%feature("docstring") itk::simple::CheckerBoardImageFilter "
5181
Combines two images in a checkerboard pattern.
5184
CheckerBoardImageFilter takes two input images that must have the same dimension, size,
5185
origin and spacing and produces an output image of the same size by
5186
combinining the pixels from the two input images in a checkerboard
5187
pattern. This filter is commonly used for visually comparing two
5188
images, in particular for evaluating the results of an image
5189
registration process.
5191
This filter is implemented as a multithreaded filter. It provides a
5192
ThreadedGenerateData() method for its implementation.
5198
Combine two images by alternating blocks of a checkerboard pattern
5200
itk::simple::CheckerBoard for the procedural interface
5202
itk::CheckerBoardImageFilter for the Doxygen on the original ITK class.
5206
C++ includes: sitkCheckerBoardImageFilter.h
5209
%feature("docstring") itk::simple::CheckerBoardImageFilter::CheckerBoardImageFilter "
5211
Default Constructor that takes no arguments and initializes default
5216
%feature("docstring") itk::simple::CheckerBoardImageFilter::Execute "
5218
Execute the filter on the input images
5222
%feature("docstring") itk::simple::CheckerBoardImageFilter::Execute "
5224
Execute the filter on the input images with the given parameters
5228
%feature("docstring") itk::simple::CheckerBoardImageFilter::GetCheckerPattern "
5230
Set/Get the checker pattern array, i.e. the number of checker boxes
5231
per image dimension.
5235
%feature("docstring") itk::simple::CheckerBoardImageFilter::GetName "
5241
%feature("docstring") itk::simple::CheckerBoardImageFilter::SetCheckerPattern "
5243
Set/Get the checker pattern array, i.e. the number of checker boxes
5244
per image dimension.
5248
%feature("docstring") itk::simple::CheckerBoardImageFilter::SetCheckerPattern "
5250
Set the values of the CheckerPattern vector all to value
5254
%feature("docstring") itk::simple::CheckerBoardImageFilter::ToString "
5260
%feature("docstring") itk::simple::CheckerBoardImageFilter::~CheckerBoardImageFilter "
5267
%feature("docstring") itk::simple::ClampImageFilter "
5269
Casts input pixels to output pixel type and clamps the output pixel
5270
values to a specified range.
5273
Default range corresponds to the range supported by the pixel type of
5276
This filter is templated over the input image type and the output
5280
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
5281
de Jouy-en-Josas, France.
5284
UnaryFunctorImageFilter
5291
Cast an image from one type to another but clamp to the output value
5294
itk::simple::Clamp for the procedural interface
5296
itk::ClampImageFilter for the Doxygen on the original ITK class.
5300
C++ includes: sitkClampImageFilter.h
5303
%feature("docstring") itk::simple::ClampImageFilter::ClampImageFilter "
5305
Default Constructor that takes no arguments and initializes default
5310
%feature("docstring") itk::simple::ClampImageFilter::Execute "
5312
Execute the filter on the input image
5316
%feature("docstring") itk::simple::ClampImageFilter::Execute "
5318
Execute the filter on the input image with the given parameters
5322
%feature("docstring") itk::simple::ClampImageFilter::GetLowerBound "
5325
%feature("docstring") itk::simple::ClampImageFilter::GetName "
5331
%feature("docstring") itk::simple::ClampImageFilter::GetOutputPixelType "
5334
%feature("docstring") itk::simple::ClampImageFilter::GetUpperBound "
5337
%feature("docstring") itk::simple::ClampImageFilter::SetLowerBound "
5340
%feature("docstring") itk::simple::ClampImageFilter::SetOutputPixelType "
5343
%feature("docstring") itk::simple::ClampImageFilter::SetUpperBound "
5346
%feature("docstring") itk::simple::ClampImageFilter::ToString "
5352
%feature("docstring") itk::simple::ClampImageFilter::~ClampImageFilter "
5359
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter "
5361
Closing by reconstruction of an image.
5364
This filter is similar to the morphological closing, but contrary to
5365
the mophological closing, the closing by reconstruction preserves the
5366
shape of the components. The closing by reconstruction of an image
5367
\"f\" is defined as:
5369
ClosingByReconstruction(f) = ErosionByReconstruction(f, Dilation(f)).
5371
Closing by reconstruction not only preserves structures preserved by
5372
the dilation, but also levels raises the contrast of the darkest
5373
regions. If PreserveIntensities is on, a subsequent reconstruction by
5374
dilation using a marker image that is the original image for all
5377
Closing by reconstruction is described in Chapter 6.3.9 of Pierre
5378
Soille's book \"Morphological Image Analysis: Principles and
5379
Applications\", Second Edition, Springer, 2003.
5382
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
5383
de Jouy-en-Josas, France.
5386
GrayscaleMorphologicalClosingImageFilter
5388
itk::simple::ClosingByReconstruction for the procedural interface
5390
itk::ClosingByReconstructionImageFilter for the Doxygen on the original ITK class.
5393
C++ includes: sitkClosingByReconstructionImageFilter.h
5396
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::ClosingByReconstructionImageFilter "
5398
Default Constructor that takes no arguments and initializes default
5403
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::Execute "
5405
Execute the filter on the input image
5409
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::Execute "
5411
Execute the filter on the input image with the given parameters
5415
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::FullyConnectedOff "
5418
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::FullyConnectedOn "
5420
Set the value of FullyConnected to true or false respectfully.
5424
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::GetFullyConnected "
5426
Set/Get whether the connected components are defined strictly by face
5427
connectivity or by face+edge+vertex connectivity. Default is
5428
FullyConnectedOff. For objects that are 1 pixel wide, use
5433
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::GetKernelRadius "
5436
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::GetKernelType "
5439
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::GetName "
5445
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::GetPreserveIntensities "
5447
Set/Get whether the original intensities of the image retained for
5448
those pixels unaffected by the opening by reconstrcution. If Off, the
5449
output pixel contrast will be reduced.
5453
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::PreserveIntensitiesOff "
5456
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::PreserveIntensitiesOn "
5458
Set the value of PreserveIntensities to true or false respectfully.
5462
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetFullyConnected "
5464
Set/Get whether the connected components are defined strictly by face
5465
connectivity or by face+edge+vertex connectivity. Default is
5466
FullyConnectedOff. For objects that are 1 pixel wide, use
5471
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetKernelRadius "
5473
Kernel radius as a scale for isotropic structures
5477
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetKernelRadius "
5479
Set/Get the radius of the kernel structuring element as a vector.
5481
If the dimension of the image is greater then the length of r, then
5482
the radius will be padded. If it is less the r will be truncated.
5486
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetKernelType "
5488
Set/Get the kernel or structuring elemenent used for the morphology
5492
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetKernelType "
5495
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::SetPreserveIntensities "
5497
Set/Get whether the original intensities of the image retained for
5498
those pixels unaffected by the opening by reconstrcution. If Off, the
5499
output pixel contrast will be reduced.
5503
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::ToString "
5509
%feature("docstring") itk::simple::ClosingByReconstructionImageFilter::~ClosingByReconstructionImageFilter "
5516
%feature("docstring") itk::simple::CollidingFrontsImageFilter "
5518
Selects a region of space where two independent fronts run towards
5522
The filter can be used to quickly segment anatomical structures (e.g.
5523
for level set initialization).
5525
The filter uses two instances of FastMarchingUpwindGradientImageFilter to compute the gradients of arrival times of two wavefronts
5526
propagating from two sets of seeds. The input of the filter is used as
5527
the speed of the two wavefronts. The output is the dot product between
5528
the two gradient vector fields.
5530
The filter works on the following basic idea. In the regions where the
5531
dot product between the two gradient fields is negative, the two
5532
fronts propagate in opposite directions. In the regions where the dot
5533
product is positive, the two fronts propagate in the same direction.
5534
This can be used to extract the region of space between two sets of
5537
If StopOnTargets is On, then each front will stop as soon as all seeds
5538
of the other front have been reached. This can markedly speed up the
5539
execution of the filter, since wave propagation does not take place on
5542
Optionally, a connectivity criterion can be applied to the resulting
5543
dot product image. In this case, the only negative region in the
5544
output image is the one connected to the seeds.
5547
Luca Antiga Ph.D. Biomedical Technologies Laboratory, Bioengineering
5548
Department, Mario Negri Institute, Italy.
5551
itk::simple::CollidingFronts for the procedural interface
5553
itk::CollidingFrontsImageFilter for the Doxygen on the original ITK class.
5556
C++ includes: sitkCollidingFrontsImageFilter.h
5559
%feature("docstring") itk::simple::CollidingFrontsImageFilter::AddSeedPoint1 "
5561
Add SeedPoints1 point.
5565
%feature("docstring") itk::simple::CollidingFrontsImageFilter::AddSeedPoint2 "
5567
Add SeedPoints2 point.
5571
%feature("docstring") itk::simple::CollidingFrontsImageFilter::ApplyConnectivityOff "
5574
%feature("docstring") itk::simple::CollidingFrontsImageFilter::ApplyConnectivityOn "
5576
Set the value of ApplyConnectivity to true or false respectfully.
5580
%feature("docstring") itk::simple::CollidingFrontsImageFilter::ClearSeedPoints1 "
5582
Remove all SeedPoints1 points.
5586
%feature("docstring") itk::simple::CollidingFrontsImageFilter::ClearSeedPoints2 "
5588
Remove all SeedPoints2 points.
5592
%feature("docstring") itk::simple::CollidingFrontsImageFilter::CollidingFrontsImageFilter "
5594
Default Constructor that takes no arguments and initializes default
5599
%feature("docstring") itk::simple::CollidingFrontsImageFilter::Execute "
5601
Execute the filter on the input image
5605
%feature("docstring") itk::simple::CollidingFrontsImageFilter::Execute "
5607
Execute the filter on the input image with the given parameters
5611
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetApplyConnectivity "
5614
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetName "
5620
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetNegativeEpsilon "
5623
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetSeedPoints1 "
5625
Get the container of Seed Points representing the first initial front.
5629
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetSeedPoints2 "
5631
Get the container of Seed Points representing the second initial
5636
%feature("docstring") itk::simple::CollidingFrontsImageFilter::GetStopOnTargets "
5639
%feature("docstring") itk::simple::CollidingFrontsImageFilter::SetApplyConnectivity "
5642
%feature("docstring") itk::simple::CollidingFrontsImageFilter::SetNegativeEpsilon "
5645
%feature("docstring") itk::simple::CollidingFrontsImageFilter::SetSeedPoints1 "
5647
Set the container of Seed Points representing the first initial front.
5648
Seed points are represented as a VectorContainer of LevelSetNodes.
5652
%feature("docstring") itk::simple::CollidingFrontsImageFilter::SetSeedPoints2 "
5654
Set the container of Seed Points representing the second initial
5655
front. Seed points are represented as a VectorContainer of LevelSetNodes.
5659
%feature("docstring") itk::simple::CollidingFrontsImageFilter::SetStopOnTargets "
5662
%feature("docstring") itk::simple::CollidingFrontsImageFilter::StopOnTargetsOff "
5665
%feature("docstring") itk::simple::CollidingFrontsImageFilter::StopOnTargetsOn "
5667
Set the value of StopOnTargets to true or false respectfully.
5671
%feature("docstring") itk::simple::CollidingFrontsImageFilter::ToString "
5677
%feature("docstring") itk::simple::CollidingFrontsImageFilter::~CollidingFrontsImageFilter "
5684
%feature("docstring") itk::simple::Command "
5686
An implementation of the Command design pattern for callback.
5689
This class provides a callback mechanism for event that occur from the ProcessObject. These commands can be utilized to observe these events.
5691
The Command can be created on the stack, and will automatically unregistered it's
5692
self when destroyed.
5694
For more information see the page Commands and Events for SimpleITK.
5696
C++ includes: sitkCommand.h
5699
%feature("docstring") itk::simple::Command::Command "
5701
Default Constructor.
5705
%feature("docstring") itk::simple::Command::Execute "
5707
The method that defines action to be taken by the command
5711
%feature("docstring") itk::simple::Command::GetName "
5713
Set/Get Command Name
5717
%feature("docstring") itk::simple::Command::SetName "
5720
%feature("docstring") itk::simple::Command::~Command "
5727
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter "
5729
Computes pixel-wise the imaginary part of a complex image.
5734
itk::simple::ComplexToImaginary for the procedural interface
5736
itk::ComplexToImaginaryImageFilter for the Doxygen on the original ITK class.
5739
C++ includes: sitkComplexToImaginaryImageFilter.h
5742
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter::ComplexToImaginaryImageFilter "
5744
Default Constructor that takes no arguments and initializes default
5749
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter::Execute "
5751
Execute the filter on the input image
5755
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter::GetName "
5761
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter::ToString "
5767
%feature("docstring") itk::simple::ComplexToImaginaryImageFilter::~ComplexToImaginaryImageFilter "
5774
%feature("docstring") itk::simple::ComplexToModulusImageFilter "
5776
Computes pixel-wise the Modulus of a complex image.
5781
itk::simple::ComplexToModulus for the procedural interface
5783
itk::ComplexToModulusImageFilter for the Doxygen on the original ITK class.
5786
C++ includes: sitkComplexToModulusImageFilter.h
5789
%feature("docstring") itk::simple::ComplexToModulusImageFilter::ComplexToModulusImageFilter "
5791
Default Constructor that takes no arguments and initializes default
5796
%feature("docstring") itk::simple::ComplexToModulusImageFilter::Execute "
5798
Execute the filter on the input image
5802
%feature("docstring") itk::simple::ComplexToModulusImageFilter::GetName "
5808
%feature("docstring") itk::simple::ComplexToModulusImageFilter::ToString "
5814
%feature("docstring") itk::simple::ComplexToModulusImageFilter::~ComplexToModulusImageFilter "
5821
%feature("docstring") itk::simple::ComplexToPhaseImageFilter "
5823
Computes pixel-wise the modulus of a complex image.
5828
itk::simple::ComplexToPhase for the procedural interface
5830
itk::ComplexToPhaseImageFilter for the Doxygen on the original ITK class.
5833
C++ includes: sitkComplexToPhaseImageFilter.h
5836
%feature("docstring") itk::simple::ComplexToPhaseImageFilter::ComplexToPhaseImageFilter "
5838
Default Constructor that takes no arguments and initializes default
5843
%feature("docstring") itk::simple::ComplexToPhaseImageFilter::Execute "
5845
Execute the filter on the input image
5849
%feature("docstring") itk::simple::ComplexToPhaseImageFilter::GetName "
5855
%feature("docstring") itk::simple::ComplexToPhaseImageFilter::ToString "
5861
%feature("docstring") itk::simple::ComplexToPhaseImageFilter::~ComplexToPhaseImageFilter "
5868
%feature("docstring") itk::simple::ComplexToRealImageFilter "
5870
Computes pixel-wise the real(x) part of a complex image.
5875
itk::simple::ComplexToReal for the procedural interface
5877
itk::ComplexToRealImageFilter for the Doxygen on the original ITK class.
5880
C++ includes: sitkComplexToRealImageFilter.h
5883
%feature("docstring") itk::simple::ComplexToRealImageFilter::ComplexToRealImageFilter "
5885
Default Constructor that takes no arguments and initializes default
5890
%feature("docstring") itk::simple::ComplexToRealImageFilter::Execute "
5892
Execute the filter on the input image
5896
%feature("docstring") itk::simple::ComplexToRealImageFilter::GetName "
5902
%feature("docstring") itk::simple::ComplexToRealImageFilter::ToString "
5908
%feature("docstring") itk::simple::ComplexToRealImageFilter::~ComplexToRealImageFilter "
5915
%feature("docstring") itk::simple::ComposeImageFilter "
5917
ComposeImageFilter combine several scalar images into a multicomponent image.
5920
ComposeImageFilter combine several scalar images into an itk::Image of vector pixel ( itk::Vector , itk::RGBPixel , ...), of std::complex pixel, or in an itk::VectorImage .
5923
All input images are expected to have the same template parameters
5924
and have the same size and origin.
5929
VectorIndexSelectionCastImageFilter
5934
Create a vector image from a collection of scalar images
5936
Compose a vector image (with 3 components) from three scalar images
5938
Convert a real image and an imaginary image to a complex image
5941
itk::simple::Compose for the procedural interface
5944
C++ includes: sitkComposeImageFilter.h
5947
%feature("docstring") itk::simple::ComposeImageFilter::ComposeImageFilter "
5949
Default Constructor that takes no arguments and initializes default
5954
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5956
Execute the filter on the input images
5960
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5963
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5966
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5969
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5972
%feature("docstring") itk::simple::ComposeImageFilter::Execute "
5975
%feature("docstring") itk::simple::ComposeImageFilter::GetName "
5981
%feature("docstring") itk::simple::ComposeImageFilter::ToString "
5987
%feature("docstring") itk::simple::ComposeImageFilter::~ComposeImageFilter "
5994
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter "
5996
Segment pixels with similar statistics using connectivity.
5999
This filter extracts a connected set of pixels whose pixel intensities
6000
are consistent with the pixel statistics of a seed point. The mean and
6001
variance across a neighborhood (8-connected, 26-connected, etc.) are
6002
calculated for a seed point. Then pixels connected to this seed point
6003
whose values are within the confidence interval for the seed point are
6004
grouped. The width of the confidence interval is controlled by the
6005
\"Multiplier\" variable (the confidence interval is the mean plus or
6006
minus the \"Multiplier\" times the standard deviation). If the
6007
intensity variations across a segment were gaussian, a \"Multiplier\"
6008
setting of 2.5 would define a confidence interval wide enough to
6009
capture 99% of samples in the segment.
6011
After this initial segmentation is calculated, the mean and variance
6012
are re-calculated. All the pixels in the previous segmentation are
6013
used to calculate the mean the standard deviation (as opposed to using
6014
the pixels in the neighborhood of the seed point). The segmentation is
6015
then recalculated using these refined estimates for the mean and
6016
variance of the pixel values. This process is repeated for the
6017
specified number of iterations. Setting the \"NumberOfIterations\" to
6018
zero stops the algorithm after the initial segmentation from the seed
6021
NOTE: the lower and upper threshold are restricted to lie within the
6022
valid numeric limits of the input data pixel type. Also, the limits
6023
may be adjusted to contain the seed point's intensity.
6029
Segment pixels with similar statistics using connectivity
6031
itk::simple::ConfidenceConnected for the procedural interface
6033
itk::ConfidenceConnectedImageFilter for the Doxygen on the original ITK class.
6037
C++ includes: sitkConfidenceConnectedImageFilter.h
6040
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::AddSeed "
6042
AddSeed - Add a seed to the end of the list
6046
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::ClearSeeds "
6048
ClearSeeds - Clear out all seeds in the list
6052
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::ConfidenceConnectedImageFilter "
6054
Default Constructor that takes no arguments and initializes default
6059
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::Execute "
6061
Execute the filter on the input image
6065
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::Execute "
6067
Execute the filter on the input image with the given parameters
6071
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetInitialNeighborhoodRadius "
6073
Get/Set the radius of the neighborhood over which the statistics are
6078
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetMean "
6080
Method to get access to the mean of the pixels accepted in the output
6081
region. This method should only be invoked after the filter has been
6082
executed using the Update() method.
6084
This is a measurement. Its value is updated in the Execute methods, so
6085
the value will only be valid after an execution.
6089
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetMultiplier "
6091
Set/Get the multiplier to define the confidence interval. Multiplier
6092
can be anything greater than zero. A typical value is 2.5
6096
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetName "
6102
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetNumberOfIterations "
6104
Set/Get the number of iterations
6108
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetReplaceValue "
6110
Set/Get value to replace thresholded pixels
6114
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetSeedList "
6120
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::GetVariance "
6122
Method to get access to the variance of the pixels accepted in the
6123
output region. This method should only be invoked after the filter has
6124
been executed using the Update() method.
6126
This is a measurement. Its value is updated in the Execute methods, so
6127
the value will only be valid after an execution.
6131
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetInitialNeighborhoodRadius "
6133
Get/Set the radius of the neighborhood over which the statistics are
6138
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetMultiplier "
6140
Set/Get the multiplier to define the confidence interval. Multiplier
6141
can be anything greater than zero. A typical value is 2.5
6145
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetNumberOfIterations "
6147
Set/Get the number of iterations
6151
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetReplaceValue "
6153
Set/Get value to replace thresholded pixels
6157
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetSeed "
6159
SetSeed - Set list to a single seed
6163
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::SetSeedList "
6169
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::ToString "
6175
%feature("docstring") itk::simple::ConfidenceConnectedImageFilter::~ConfidenceConnectedImageFilter "
6182
%feature("docstring") itk::simple::ConnectedComponentImageFilter "
6184
Label the objects in a binary image.
6187
ConnectedComponentImageFilter labels the objects in a binary image (non-zero pixels are considered
6188
to be objects, zero-valued pixels are considered to be background).
6189
Each distinct object is assigned a unique label. The filter
6190
experiments with some improvements to the existing implementation, and
6191
is based on run length encoding along raster lines. The final object
6192
labels start with 1 and are consecutive. Objects that are reached
6193
earlier by a raster order scan have a lower label. This is different
6194
to the behaviour of the original connected component image filter
6195
which did not produce consecutive labels or impose any particular
6198
After the filter is executed, ObjectCount holds the number of
6199
connected components.
6208
Label connected components in a binary image
6210
itk::simple::ConnectedComponent for the procedural interface
6212
itk::ConnectedComponentImageFilter for the Doxygen on the original ITK class.
6216
C++ includes: sitkConnectedComponentImageFilter.h
6219
%feature("docstring") itk::simple::ConnectedComponentImageFilter::ConnectedComponentImageFilter "
6221
Default Constructor that takes no arguments and initializes default
6226
%feature("docstring") itk::simple::ConnectedComponentImageFilter::Execute "
6228
Execute the filter on the input image
6232
%feature("docstring") itk::simple::ConnectedComponentImageFilter::Execute "
6234
Execute the filter on the input image with the given parameters
6238
%feature("docstring") itk::simple::ConnectedComponentImageFilter::FullyConnectedOff "
6241
%feature("docstring") itk::simple::ConnectedComponentImageFilter::FullyConnectedOn "
6243
Set the value of FullyConnected to true or false respectfully.
6247
%feature("docstring") itk::simple::ConnectedComponentImageFilter::GetFullyConnected "
6249
Set/Get whether the connected components are defined strictly by face
6250
connectivity or by face+edge+vertex connectivity. Default is
6251
FullyConnectedOff. For objects that are 1 pixel wide, use
6256
%feature("docstring") itk::simple::ConnectedComponentImageFilter::GetName "
6262
%feature("docstring") itk::simple::ConnectedComponentImageFilter::GetObjectCount "
6264
This is a measurement. Its value is updated in the Execute methods, so
6265
the value will only be valid after an execution.
6269
%feature("docstring") itk::simple::ConnectedComponentImageFilter::SetFullyConnected "
6271
Set/Get whether the connected components are defined strictly by face
6272
connectivity or by face+edge+vertex connectivity. Default is
6273
FullyConnectedOff. For objects that are 1 pixel wide, use
6278
%feature("docstring") itk::simple::ConnectedComponentImageFilter::ToString "
6284
%feature("docstring") itk::simple::ConnectedComponentImageFilter::~ConnectedComponentImageFilter "
6291
%feature("docstring") itk::simple::ConnectedThresholdImageFilter "
6293
Label pixels that are connected to a seed and lie within a range of
6297
ConnectedThresholdImageFilter labels pixels with ReplaceValue that are connected to an initial Seed
6298
AND lie within a Lower and Upper threshold range.
6300
itk::simple::ConnectedThreshold for the procedural interface
6302
itk::ConnectedThresholdImageFilter for the Doxygen on the original ITK class.
6305
C++ includes: sitkConnectedThresholdImageFilter.h
6308
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::AddSeed "
6310
AddSeed - Add a seed to the end of the list
6314
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::ClearSeeds "
6316
ClearSeeds - Clear out all seeds in the list
6320
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::ConnectedThresholdImageFilter "
6322
Default Constructor that takes no arguments and initializes default
6327
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::Execute "
6329
Execute the filter on the input image
6333
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::Execute "
6335
Execute the filter on the input image with the given parameters
6339
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetConnectivity "
6341
Type of connectivity to use (fully connected OR 4(2D), 6(3D), 2*N(ND)
6346
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetLower "
6348
Get Upper and Lower Threshold inputs as values.
6352
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetName "
6358
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetReplaceValue "
6360
Set/Get value to replace thresholded pixels. Pixels that lie * within
6361
Lower and Upper (inclusive) will be replaced with this value. The
6366
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetSeedList "
6372
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::GetUpper "
6374
Get Upper and Lower Threshold inputs as values.
6378
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetConnectivity "
6380
Type of connectivity to use (fully connected OR 4(2D), 6(3D), 2*N(ND)
6385
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetLower "
6387
Set Upper and Lower Threshold inputs as values
6391
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetReplaceValue "
6393
Set/Get value to replace thresholded pixels. Pixels that lie * within
6394
Lower and Upper (inclusive) will be replaced with this value. The
6399
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetSeed "
6401
SetSeed - Set list to a single seed
6405
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetSeedList "
6411
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::SetUpper "
6413
Set Upper and Lower Threshold inputs as values
6417
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::ToString "
6423
%feature("docstring") itk::simple::ConnectedThresholdImageFilter::~ConnectedThresholdImageFilter "
6430
%feature("docstring") itk::simple::ConstantPadImageFilter "
6432
Increase the image size by padding with a constant value.
6435
ConstantPadImageFilter changes the output image region. If the output image region is larger
6436
than the input image region, the extra pixels are filled in by a
6437
constant value. The output image region must be specified.
6439
Visual explanation of padding regions. This filter is implemented as a
6440
multithreaded filter. It provides a ThreadedGenerateData() method for
6445
WrapPadImageFilter , MirrorPadImageFilter
6450
Pad an image with a constant value
6452
itk::simple::ConstantPad for the procedural interface
6454
itk::ConstantPadImageFilter for the Doxygen on the original ITK class.
6458
C++ includes: sitkConstantPadImageFilter.h
6461
%feature("docstring") itk::simple::ConstantPadImageFilter::ConstantPadImageFilter "
6463
Default Constructor that takes no arguments and initializes default
6468
%feature("docstring") itk::simple::ConstantPadImageFilter::Execute "
6470
Execute the filter on the input image
6474
%feature("docstring") itk::simple::ConstantPadImageFilter::Execute "
6476
Execute the filter on the input image with the given parameters
6480
%feature("docstring") itk::simple::ConstantPadImageFilter::GetConstant "
6482
Set/Get the pad value. Default is Zero.
6486
%feature("docstring") itk::simple::ConstantPadImageFilter::GetName "
6492
%feature("docstring") itk::simple::ConstantPadImageFilter::GetPadLowerBound "
6495
%feature("docstring") itk::simple::ConstantPadImageFilter::GetPadUpperBound "
6498
%feature("docstring") itk::simple::ConstantPadImageFilter::SetConstant "
6500
Set/Get the pad value. Default is Zero.
6504
%feature("docstring") itk::simple::ConstantPadImageFilter::SetPadLowerBound "
6507
%feature("docstring") itk::simple::ConstantPadImageFilter::SetPadUpperBound "
6510
%feature("docstring") itk::simple::ConstantPadImageFilter::ToString "
6516
%feature("docstring") itk::simple::ConstantPadImageFilter::~ConstantPadImageFilter "
6523
%feature("docstring") itk::simple::ConvolutionImageFilter "
6525
Convolve a given image with an arbitrary image kernel.
6528
This filter operates by centering the flipped kernel at each pixel in
6529
the image and computing the inner product between pixel values in the
6530
image and pixel values in the kernel. The center of the kernel is
6531
defined as $ \\\\lfloor (2*i+s-1)/2 \\\\rfloor $ where $i$ is the index and $s$ is the size of the largest possible region of the kernel image. For
6532
kernels with odd sizes in all dimensions, this corresponds to the
6533
center pixel. If a dimension of the kernel image has an even size,
6534
then the center index of the kernel in that dimension will be the
6535
largest integral index that is less than the continuous index of the
6538
The kernel can optionally be normalized to sum to 1 using NormalizeOn() . Normalization is off by default.
6542
This filter ignores the spacing, origin, and orientation of the kernel
6543
image and treats them as identical to those in the input image.
6544
This code was contributed in the Insight Journal paper:
6546
\"Image Kernel Convolution\" by Tustison N., Gee J. https://hdl.handle.net/1926/1323 http://www.insight-journal.org/browse/publication/208
6549
Nicholas J. Tustison
6556
Convolve an image with a kernel
6558
itk::simple::Convolution for the procedural interface
6560
itk::ConvolutionImageFilter for the Doxygen on the original ITK class.
6564
C++ includes: sitkConvolutionImageFilter.h
6567
%feature("docstring") itk::simple::ConvolutionImageFilter::ConvolutionImageFilter "
6569
Default Constructor that takes no arguments and initializes default
6574
%feature("docstring") itk::simple::ConvolutionImageFilter::Execute "
6576
Execute the filter on the input images
6580
%feature("docstring") itk::simple::ConvolutionImageFilter::Execute "
6582
Execute the filter on the input images with the given parameters
6586
%feature("docstring") itk::simple::ConvolutionImageFilter::GetBoundaryCondition "
6589
%feature("docstring") itk::simple::ConvolutionImageFilter::GetName "
6595
%feature("docstring") itk::simple::ConvolutionImageFilter::GetNormalize "
6598
%feature("docstring") itk::simple::ConvolutionImageFilter::GetOutputRegionMode "
6601
%feature("docstring") itk::simple::ConvolutionImageFilter::NormalizeOff "
6604
%feature("docstring") itk::simple::ConvolutionImageFilter::NormalizeOn "
6606
Set the value of Normalize to true or false respectfully.
6610
%feature("docstring") itk::simple::ConvolutionImageFilter::SetBoundaryCondition "
6613
%feature("docstring") itk::simple::ConvolutionImageFilter::SetNormalize "
6615
Normalize the output image by the sum of the kernel components
6619
%feature("docstring") itk::simple::ConvolutionImageFilter::SetOutputRegionMode "
6622
%feature("docstring") itk::simple::ConvolutionImageFilter::ToString "
6628
%feature("docstring") itk::simple::ConvolutionImageFilter::~ConvolutionImageFilter "
6635
%feature("docstring") itk::simple::CosImageFilter "
6637
Computes the cosine of each pixel.
6640
This filter is templated over the pixel type of the input image and
6641
the pixel type of the output image.
6643
The filter walks over all of the pixels in the input image, and for
6644
each pixel does the following:
6647
cast the pixel value to double ,
6649
apply the std::cos() function to the double value,
6651
cast the double value resulting from std::cos() to the pixel type of
6654
store the cast value into the output image.
6655
The filter expects both images to have the same dimension (e.g. both
6656
2D, or both 3D, or both ND)
6658
itk::simple::Cos for the procedural interface
6660
itk::CosImageFilter for the Doxygen on the original ITK class.
6663
C++ includes: sitkCosImageFilter.h
6666
%feature("docstring") itk::simple::CosImageFilter::CosImageFilter "
6668
Default Constructor that takes no arguments and initializes default
6673
%feature("docstring") itk::simple::CosImageFilter::Execute "
6675
Execute the filter on the input image
6679
%feature("docstring") itk::simple::CosImageFilter::GetName "
6685
%feature("docstring") itk::simple::CosImageFilter::ToString "
6691
%feature("docstring") itk::simple::CosImageFilter::~CosImageFilter "
6698
%feature("docstring") itk::simple::CropImageFilter "
6700
Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region.
6703
CropImageFilter changes the image boundary of an image by removing pixels outside the
6704
target region. The target region is not specified in advance, but
6705
calculated in BeforeThreadedGenerateData() .
6707
This filter uses ExtractImageFilter to perform the cropping.
6713
Crop an image by specifying the region to throw away
6715
itk::simple::Crop for the procedural interface
6717
itk::CropImageFilter for the Doxygen on the original ITK class.
6721
C++ includes: sitkCropImageFilter.h
6724
%feature("docstring") itk::simple::CropImageFilter::CropImageFilter "
6726
Default Constructor that takes no arguments and initializes default
6731
%feature("docstring") itk::simple::CropImageFilter::Execute "
6733
Execute the filter on the input image
6737
%feature("docstring") itk::simple::CropImageFilter::Execute "
6739
Execute the filter on the input image with the given parameters
6743
%feature("docstring") itk::simple::CropImageFilter::GetLowerBoundaryCropSize "
6745
Set/Get the cropping sizes for the upper and lower boundaries.
6749
%feature("docstring") itk::simple::CropImageFilter::GetName "
6755
%feature("docstring") itk::simple::CropImageFilter::GetUpperBoundaryCropSize "
6757
Set/Get the cropping sizes for the upper and lower boundaries.
6761
%feature("docstring") itk::simple::CropImageFilter::SetLowerBoundaryCropSize "
6763
Set/Get the cropping sizes for the upper and lower boundaries.
6767
%feature("docstring") itk::simple::CropImageFilter::SetUpperBoundaryCropSize "
6769
Set/Get the cropping sizes for the upper and lower boundaries.
6773
%feature("docstring") itk::simple::CropImageFilter::ToString "
6779
%feature("docstring") itk::simple::CropImageFilter::~CropImageFilter "
6786
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter "
6788
This filter performs anisotropic diffusion on a scalar itk::Image using the modified curvature diffusion equation (MCDE) implemented in
6789
itkCurvatureNDAnisotropicDiffusionFunction. For detailed information
6790
on anisotropic diffusion and the MCDE see
6791
itkAnisotropicDiffusionFunction and
6792
itkCurvatureNDAnisotropicDiffusionFunction.
6795
The input and output to this filter must be a scalar itk::Image with numerical pixel types (float or double). A user defined type
6796
which correctly defines arithmetic operations with floating point
6797
accuracy should also give correct results.
6799
Please first read all the documentation found in AnisotropicDiffusionImageFilter and AnisotropicDiffusionFunction . Also see CurvatureNDAnisotropicDiffusionFunction .
6800
The default time step for this filter is set to the maximum
6801
theoretically stable value: 0.5 / 2^N, where N is the dimensionality
6802
of the image. For a 2D image, this means valid time steps are below
6803
0.1250. For a 3D image, valid time steps are below 0.0625.
6807
AnisotropicDiffusionImageFilter
6809
AnisotropicDiffusionFunction
6811
CurvatureNDAnisotropicDiffusionFunction
6813
itk::simple::CurvatureAnisotropicDiffusion for the procedural interface
6815
itk::CurvatureAnisotropicDiffusionImageFilter for the Doxygen on the original ITK class.
6818
C++ includes: sitkCurvatureAnisotropicDiffusionImageFilter.h
6821
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::CurvatureAnisotropicDiffusionImageFilter "
6823
Default Constructor that takes no arguments and initializes default
6828
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::EstimateOptimalTimeStep "
6830
This method autmatically sets the optimal timestep for an image given
6835
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::Execute "
6837
Execute the filter on the input image
6841
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::Execute "
6843
Execute the filter on the input image with the given parameters
6847
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::GetConductanceParameter "
6850
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::GetConductanceScalingUpdateInterval "
6853
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::GetName "
6859
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::GetNumberOfIterations "
6862
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::GetTimeStep "
6865
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::SetConductanceParameter "
6868
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::SetConductanceScalingUpdateInterval "
6871
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::SetNumberOfIterations "
6874
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::SetTimeStep "
6877
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::ToString "
6883
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusionImageFilter::~CurvatureAnisotropicDiffusionImageFilter "
6890
%feature("docstring") itk::simple::CurvatureFlowImageFilter "
6892
Denoise an image using curvature driven flow.
6895
CurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-
6896
brightness contours in the grayscale input image are viewed as a level
6897
set. The level set is then evolved using a curvature-based speed
6900
\\\\[ I_t = \\\\kappa |\\\\nabla I| \\\\] where $ \\\\kappa $ is the curvature.
6902
The advantage of this approach is that sharp boundaries are preserved
6903
with smoothing occurring only within a region. However, it should be
6904
noted that continuous application of this scheme will result in the
6905
eventual removal of all information as each contour shrinks to zero
6908
Note that unlike level set segmentation algorithms, the image to be
6909
denoised is already the level set and can be set directly as the input
6910
using the SetInput() method.
6912
This filter has two parameters: the number of update iterations to be
6913
performed and the timestep between each update.
6915
The timestep should be \"small enough\" to ensure numerical stability.
6916
Stability is guarantee when the timestep meets the CFL (Courant-
6917
Friedrichs-Levy) condition. Broadly speaking, this condition ensures
6918
that each contour does not move more than one grid position at each
6919
timestep. In the literature, the timestep is typically user specified
6920
and have to manually tuned to the application.
6922
This filter make use of the multi-threaded finite difference solver
6923
hierarchy. Updates are computed using a CurvatureFlowFunction object. A zero flux Neumann boundary condition when computing
6924
derivatives near the data boundary.
6926
This filter may be streamed. To support streaming this filter produces
6927
a padded output which takes into account edge effects. The size of the
6928
padding is m_NumberOfIterations on each edge. Users of this filter
6929
should only make use of the center valid central region.
6933
This filter assumes that the input and output types have the same
6934
dimensions. This filter also requires that the output image pixels are
6935
of a floating point type. This filter works for any dimensional
6937
Reference: \"Level Set Methods and Fast Marching Methods\", J.A.
6938
Sethian, Cambridge Press, Chapter 16, Second edition, 1999.
6942
DenseFiniteDifferenceImageFilter
6944
CurvatureFlowFunction
6946
MinMaxCurvatureFlowImageFilter
6948
BinaryMinMaxCurvatureFlowImageFilter
6950
itk::simple::CurvatureFlow for the procedural interface
6952
itk::CurvatureFlowImageFilter for the Doxygen on the original ITK class.
6955
C++ includes: sitkCurvatureFlowImageFilter.h
6958
%feature("docstring") itk::simple::CurvatureFlowImageFilter::CurvatureFlowImageFilter "
6960
Default Constructor that takes no arguments and initializes default
6965
%feature("docstring") itk::simple::CurvatureFlowImageFilter::Execute "
6967
Execute the filter on the input image
6971
%feature("docstring") itk::simple::CurvatureFlowImageFilter::Execute "
6973
Execute the filter on the input image with the given parameters
6977
%feature("docstring") itk::simple::CurvatureFlowImageFilter::GetName "
6983
%feature("docstring") itk::simple::CurvatureFlowImageFilter::GetNumberOfIterations "
6986
%feature("docstring") itk::simple::CurvatureFlowImageFilter::GetTimeStep "
6988
Get the timestep parameter.
6992
%feature("docstring") itk::simple::CurvatureFlowImageFilter::SetNumberOfIterations "
6995
%feature("docstring") itk::simple::CurvatureFlowImageFilter::SetTimeStep "
6997
Set the timestep parameter.
7001
%feature("docstring") itk::simple::CurvatureFlowImageFilter::ToString "
7007
%feature("docstring") itk::simple::CurvatureFlowImageFilter::~CurvatureFlowImageFilter "
7014
%feature("docstring") itk::simple::CyclicShiftImageFilter "
7016
Perform a cyclic spatial shift of image intensities on the image grid.
7019
This filter supports arbitrary cyclic shifts of pixel values on the
7020
image grid. If the Shift is set to [xOff, yOff], the value of the
7021
pixel at [0, 0] in the input image will be the value of the pixel in
7022
the output image at index [xOff modulo xSize, yOff modulo ySize] where
7023
xSize and ySize are the sizes of the image in the x and y dimensions,
7024
respectively. If a pixel value is moved across a boundary, the pixel
7025
value is wrapped around that boundary. For example, if the image is
7026
40-by-40 and the Shift is [13, 47], then the value of the pixel at [0,
7027
0] in the input image will be the value of the pixel in the output
7028
image at index [13, 7].
7030
Negative Shifts are supported. This filter also works with images
7031
whose largest possible region starts at a non-zero index.
7033
itk::simple::CyclicShift for the procedural interface
7035
itk::CyclicShiftImageFilter for the Doxygen on the original ITK class.
7038
C++ includes: sitkCyclicShiftImageFilter.h
7041
%feature("docstring") itk::simple::CyclicShiftImageFilter::CyclicShiftImageFilter "
7043
Default Constructor that takes no arguments and initializes default
7048
%feature("docstring") itk::simple::CyclicShiftImageFilter::Execute "
7050
Execute the filter on the input image
7054
%feature("docstring") itk::simple::CyclicShiftImageFilter::Execute "
7056
Execute the filter on the input image with the given parameters
7060
%feature("docstring") itk::simple::CyclicShiftImageFilter::GetName "
7066
%feature("docstring") itk::simple::CyclicShiftImageFilter::GetShift "
7068
Set/get the shift. Shifts may be positive or negative.
7072
%feature("docstring") itk::simple::CyclicShiftImageFilter::SetShift "
7074
Set/get the shift. Shifts may be positive or negative.
7078
%feature("docstring") itk::simple::CyclicShiftImageFilter::SetShift "
7080
Set the values of the Shift vector all to value
7084
%feature("docstring") itk::simple::CyclicShiftImageFilter::ToString "
7090
%feature("docstring") itk::simple::CyclicShiftImageFilter::~CyclicShiftImageFilter "
7097
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter "
7099
This filter computes the distance map of the input image as an
7100
approximation with pixel accuracy to the Euclidean distance.
7113
Voronoi Image Type. Note the default value is TInputImage.
7115
The input is assumed to contain numeric codes defining objects. The
7116
filter will produce as output the following images:
7119
A Voronoi partition using the same numeric codes as the input.
7121
A distance map with the approximation to the euclidean distance. from
7122
a particular pixel to the nearest object to this pixel in the input
7125
A vector map containing the component of the vector relating the
7126
current pixel with the closest point of the closest object to this
7127
pixel. Given that the components of the distance are computed in
7128
\"pixels\", the vector is represented by an itk::Offset . That is, physical coordinates are not used.
7129
This filter is N-dimensional and known to be efficient in
7130
computational time. The algorithm is the N-dimensional version of the
7131
4SED algorithm given for two dimensions in:
7133
Danielsson, Per-Erik. Euclidean Distance Mapping. Computer Graphics
7134
and Image Processing 14, 227-248 (1980).
7136
itk::simple::DanielssonDistanceMap for the procedural interface
7138
itk::DanielssonDistanceMapImageFilter for the Doxygen on the original ITK class.
7141
C++ includes: sitkDanielssonDistanceMapImageFilter.h
7144
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::DanielssonDistanceMapImageFilter "
7146
Default Constructor that takes no arguments and initializes default
7151
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::Execute "
7153
Execute the filter on the input image
7157
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::Execute "
7159
Execute the filter on the input image with the given parameters
7163
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::GetInputIsBinary "
7165
Get if the input is binary. See SetInputIsBinary() .
7169
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::GetName "
7175
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::GetSquaredDistance "
7177
Get the distance squared.
7181
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::GetUseImageSpacing "
7183
Get whether spacing is used.
7187
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::InputIsBinaryOff "
7190
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::InputIsBinaryOn "
7192
Set the value of InputIsBinary to true or false respectfully.
7196
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::SetInputIsBinary "
7198
Set if the input is binary. If this variable is set, each nonzero
7199
pixel in the input image will be given a unique numeric code to be
7200
used by the Voronoi partition. If the image is binary but you are not
7201
interested in the Voronoi regions of the different nonzero pixels,
7202
then you need not set this.
7206
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::SetSquaredDistance "
7208
Set if the distance should be squared.
7212
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::SetUseImageSpacing "
7214
Set if image spacing should be used in computing distances.
7218
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::SquaredDistanceOff "
7221
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::SquaredDistanceOn "
7223
Set the value of SquaredDistance to true or false respectfully.
7227
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::ToString "
7233
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::UseImageSpacingOff "
7236
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::UseImageSpacingOn "
7238
Set the value of UseImageSpacing to true or false respectfully.
7242
%feature("docstring") itk::simple::DanielssonDistanceMapImageFilter::~DanielssonDistanceMapImageFilter "
7249
%feature("docstring") itk::simple::DemonsRegistrationFilter "
7251
Deformably register two images using the demons algorithm.
7254
DemonsRegistrationFilter implements the demons deformable algorithm that register two images
7255
by computing the displacement field which will map a moving image onto
7258
A displacement field is represented as a image whose pixel type is
7259
some vector type with at least N elements, where N is the dimension of
7260
the fixed image. The vector type must support element access via
7261
operator []. It is assumed that the vector elements behave like
7262
floating point scalars.
7264
This class is templated over the fixed image type, moving image type
7265
and the displacement field type.
7267
The input fixed and moving images are set via methods SetFixedImage
7268
and SetMovingImage respectively. An initial displacement field maybe
7269
set via SetInitialDisplacementField or SetInput. If no initial field
7270
is set, a zero field is used as the initial condition.
7272
The algorithm has one parameters: the number of iteration to be
7275
The output displacement field can be obtained via methods GetOutput or
7276
GetDisplacementField.
7278
This class make use of the finite difference solver hierarchy. Update
7279
for each iteration is computed in DemonsRegistrationFunction .
7283
This filter assumes that the fixed image type, moving image type and
7284
displacement field type all have the same number of dimensions.
7287
DemonsRegistrationFunction
7289
itk::DemonsRegistrationFilter for the Doxygen on the original ITK class.
7292
C++ includes: sitkDemonsRegistrationFilter.h
7295
%feature("docstring") itk::simple::DemonsRegistrationFilter::DemonsRegistrationFilter "
7297
Default Constructor that takes no arguments and initializes default
7302
%feature("docstring") itk::simple::DemonsRegistrationFilter::Execute "
7304
Execute the filter on the input image
7308
%feature("docstring") itk::simple::DemonsRegistrationFilter::Execute "
7311
%feature("docstring") itk::simple::DemonsRegistrationFilter::Execute "
7313
Execute the filter on the input image with the given parameters
7317
%feature("docstring") itk::simple::DemonsRegistrationFilter::Execute "
7320
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetElapsedIterations "
7322
Number of iterations run.
7325
This is an active measurement. It may be accessed while the filter is
7326
being executing in command call-backs and can be accessed after
7331
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetIntensityDifferenceThreshold "
7334
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetMaximumError "
7336
Set/Get the desired maximum error of the Guassian kernel approximate.
7340
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetMaximumKernelWidth "
7342
Set/Get the desired limits of the Gaussian kernel width.
7346
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetMaximumRMSError "
7349
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetMetric "
7351
Get the metric value. The metric value is the mean square difference
7352
in intensity between the fixed image and transforming moving image
7353
computed over the the overlapping region between the two images. This
7354
is value is only available for the previous iteration and NOT the
7357
This is an active measurement. It may be accessed while the filter is
7358
being executing in command call-backs and can be accessed after
7363
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetName "
7369
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetNumberOfIterations "
7372
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetRMSChange "
7374
The Root Mean Square of the levelset upon termination.
7377
This is a measurement. Its value is updated in the Execute methods, so
7378
the value will only be valid after an execution.
7382
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetSmoothDisplacementField "
7384
Set/Get whether the displacement field is smoothed (regularized).
7385
Smoothing the displacement yields a solution elastic in nature. If
7386
SmoothDisplacementField is on, then the displacement field is smoothed
7387
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
7391
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetSmoothUpdateField "
7393
Set/Get whether the update field is smoothed (regularized). Smoothing
7394
the update field yields a solution viscous in nature. If
7395
SmoothUpdateField is on, then the update field is smoothed with a
7396
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
7400
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetStandardDeviations "
7402
Set/Get the Gaussian smoothing standard deviations for the
7403
displacement field. The values are set with respect to pixel
7408
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetUpdateFieldStandardDeviations "
7410
Set the Gaussian smoothing standard deviations for the update field.
7411
The values are set with respect to pixel coordinates.
7415
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetUseImageSpacing "
7418
%feature("docstring") itk::simple::DemonsRegistrationFilter::GetUseMovingImageGradient "
7420
Switch between using the fixed image and moving image gradient for
7421
computing the displacement field updates.
7425
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetIntensityDifferenceThreshold "
7427
Set/Get the threshold below which the absolute difference of intensity
7428
yields a match. When the intensities match between a moving and fixed
7429
image pixel, the update vector (for that iteration) will be the zero
7430
vector. Default is 0.001.
7434
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetMaximumError "
7436
Set/Get the desired maximum error of the Guassian kernel approximate.
7440
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetMaximumKernelWidth "
7442
Set/Get the desired limits of the Gaussian kernel width.
7446
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetMaximumRMSError "
7449
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetNumberOfIterations "
7452
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetSmoothDisplacementField "
7454
Set/Get whether the displacement field is smoothed (regularized).
7455
Smoothing the displacement yields a solution elastic in nature. If
7456
SmoothDisplacementField is on, then the displacement field is smoothed
7457
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
7461
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetSmoothUpdateField "
7463
Set/Get whether the update field is smoothed (regularized). Smoothing
7464
the update field yields a solution viscous in nature. If
7465
SmoothUpdateField is on, then the update field is smoothed with a
7466
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
7470
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetStandardDeviations "
7472
Set/Get the Gaussian smoothing standard deviations for the
7473
displacement field. The values are set with respect to pixel
7478
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetStandardDeviations "
7480
Set the values of the StandardDeviations vector all to value
7484
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
7486
Set the Gaussian smoothing standard deviations for the update field.
7487
The values are set with respect to pixel coordinates.
7491
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
7493
Set the values of the UpdateFieldStandardDeviations vector all to
7498
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetUseImageSpacing "
7501
%feature("docstring") itk::simple::DemonsRegistrationFilter::SetUseMovingImageGradient "
7503
Switch between using the fixed image and moving image gradient for
7504
computing the displacement field updates.
7508
%feature("docstring") itk::simple::DemonsRegistrationFilter::SmoothDisplacementFieldOff "
7511
%feature("docstring") itk::simple::DemonsRegistrationFilter::SmoothDisplacementFieldOn "
7513
Set the value of SmoothDisplacementField to true or false
7518
%feature("docstring") itk::simple::DemonsRegistrationFilter::SmoothUpdateFieldOff "
7521
%feature("docstring") itk::simple::DemonsRegistrationFilter::SmoothUpdateFieldOn "
7523
Set the value of SmoothUpdateField to true or false respectfully.
7527
%feature("docstring") itk::simple::DemonsRegistrationFilter::ToString "
7533
%feature("docstring") itk::simple::DemonsRegistrationFilter::UseImageSpacingOff "
7536
%feature("docstring") itk::simple::DemonsRegistrationFilter::UseImageSpacingOn "
7538
Set the value of UseImageSpacing to true or false respectfully.
7542
%feature("docstring") itk::simple::DemonsRegistrationFilter::UseMovingImageGradientOff "
7545
%feature("docstring") itk::simple::DemonsRegistrationFilter::UseMovingImageGradientOn "
7547
Set the value of UseMovingImageGradient to true or false respectfully.
7551
%feature("docstring") itk::simple::DemonsRegistrationFilter::~DemonsRegistrationFilter "
7558
%feature("docstring") itk::simple::DerivativeImageFilter "
7560
Computes the directional derivative of an image. The directional
7561
derivative at each pixel location is computed by convolution with a
7562
derivative operator of user-specified order.
7565
SetOrder specifies the order of the derivative.
7567
SetDirection specifies the direction of the derivative with respect to
7568
the coordinate axes of the image.
7576
NeighborhoodOperator
7578
NeighborhoodIterator
7583
Compute the derivative of an image in a particular direction
7585
itk::simple::Derivative for the procedural interface
7587
itk::DerivativeImageFilter for the Doxygen on the original ITK class.
7591
C++ includes: sitkDerivativeImageFilter.h
7594
%feature("docstring") itk::simple::DerivativeImageFilter::DerivativeImageFilter "
7596
Default Constructor that takes no arguments and initializes default
7601
%feature("docstring") itk::simple::DerivativeImageFilter::Execute "
7603
Execute the filter on the input image
7607
%feature("docstring") itk::simple::DerivativeImageFilter::Execute "
7609
Execute the filter on the input image with the given parameters
7613
%feature("docstring") itk::simple::DerivativeImageFilter::GetDirection "
7615
The output pixel type must be signed. Standard get/set macros for
7620
%feature("docstring") itk::simple::DerivativeImageFilter::GetName "
7626
%feature("docstring") itk::simple::DerivativeImageFilter::GetOrder "
7628
The output pixel type must be signed. Standard get/set macros for
7633
%feature("docstring") itk::simple::DerivativeImageFilter::GetUseImageSpacing "
7635
Set/Get whether or not the filter will use the spacing of the input
7636
image in its calculations
7640
%feature("docstring") itk::simple::DerivativeImageFilter::SetDirection "
7642
The output pixel type must be signed. Standard get/set macros for
7647
%feature("docstring") itk::simple::DerivativeImageFilter::SetOrder "
7649
The output pixel type must be signed. Standard get/set macros for
7654
%feature("docstring") itk::simple::DerivativeImageFilter::SetUseImageSpacing "
7656
Set/Get whether or not the filter will use the spacing of the input
7657
image in its calculations
7661
%feature("docstring") itk::simple::DerivativeImageFilter::ToString "
7667
%feature("docstring") itk::simple::DerivativeImageFilter::UseImageSpacingOff "
7670
%feature("docstring") itk::simple::DerivativeImageFilter::UseImageSpacingOn "
7672
Set the value of UseImageSpacing to true or false respectfully.
7676
%feature("docstring") itk::simple::DerivativeImageFilter::~DerivativeImageFilter "
7683
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter "
7685
Deformably register two images using a diffeomorphic demons algorithm.
7688
This class was contributed by Tom Vercauteren, INRIA & Mauna Kea
7689
Technologies, based on a variation of the DemonsRegistrationFilter . The basic modification is to use diffeomorphism exponentials.
7691
See T. Vercauteren, X. Pennec, A. Perchant and N. Ayache, \"Non-
7692
parametric Diffeomorphic Image Registration with the Demons
7693
Algorithm\", Proc. of MICCAI 2007.
7695
DiffeomorphicDemonsRegistrationFilter implements the demons deformable algorithm that register two images
7696
by computing the deformation field which will map a moving image onto
7699
A deformation field is represented as a image whose pixel type is some
7700
vector type with at least N elements, where N is the dimension of the
7701
fixed image. The vector type must support element access via operator
7702
[]. It is assumed that the vector elements behave like floating point
7705
This class is templated over the fixed image type, moving image type
7706
and the deformation field type.
7708
The input fixed and moving images are set via methods SetFixedImage
7709
and SetMovingImage respectively. An initial deformation field maybe
7710
set via SetInitialDisplacementField or SetInput. If no initial field
7711
is set, a zero field is used as the initial condition.
7713
The output deformation field can be obtained via methods GetOutput or
7714
GetDisplacementField.
7716
This class make use of the finite difference solver hierarchy. Update
7717
for each iteration is computed in DemonsRegistrationFunction .
7720
Tom Vercauteren, INRIA & Mauna Kea Technologies
7723
This filter assumes that the fixed image type, moving image type and
7724
deformation field type all have the same number of dimensions.
7725
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/510
7729
DemonsRegistrationFilter
7731
DemonsRegistrationFunction
7733
itk::DiffeomorphicDemonsRegistrationFilter for the Doxygen on the original ITK class.
7736
C++ includes: sitkDiffeomorphicDemonsRegistrationFilter.h
7739
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::DiffeomorphicDemonsRegistrationFilter "
7741
Default Constructor that takes no arguments and initializes default
7746
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::Execute "
7748
Execute the filter on the input image
7752
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::Execute "
7755
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::Execute "
7757
Execute the filter on the input image with the given parameters
7761
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::Execute "
7764
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetElapsedIterations "
7766
Number of iterations run.
7769
This is an active measurement. It may be accessed while the filter is
7770
being executing in command call-backs and can be accessed after
7775
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetIntensityDifferenceThreshold "
7778
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetMaximumError "
7780
Set/Get the desired maximum error of the Guassian kernel approximate.
7784
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetMaximumKernelWidth "
7786
Set/Get the desired limits of the Gaussian kernel width.
7790
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetMaximumRMSError "
7793
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetMaximumUpdateStepLength "
7796
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetMetric "
7798
Get the metric value. The metric value is the mean square difference
7799
in intensity between the fixed image and transforming moving image
7800
computed over the the overlapping region between the two images. This
7801
value is calculated for the current iteration
7803
This is an active measurement. It may be accessed while the filter is
7804
being executing in command call-backs and can be accessed after
7809
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetName "
7815
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetNumberOfIterations "
7818
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetRMSChange "
7820
Set/Get the root mean squared change of the previous iteration. May
7821
not be used by all solvers.
7823
This is a measurement. Its value is updated in the Execute methods, so
7824
the value will only be valid after an execution.
7828
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetSmoothDisplacementField "
7830
Set/Get whether the displacement field is smoothed (regularized).
7831
Smoothing the displacement yields a solution elastic in nature. If
7832
SmoothDisplacementField is on, then the displacement field is smoothed
7833
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
7837
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetSmoothUpdateField "
7839
Set/Get whether the update field is smoothed (regularized). Smoothing
7840
the update field yields a solution viscous in nature. If
7841
SmoothUpdateField is on, then the update field is smoothed with a
7842
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
7846
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetStandardDeviations "
7848
Set/Get the Gaussian smoothing standard deviations for the
7849
displacement field. The values are set with respect to pixel
7854
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetUpdateFieldStandardDeviations "
7856
Set the Gaussian smoothing standard deviations for the update field.
7857
The values are set with respect to pixel coordinates.
7861
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetUseFirstOrderExp "
7863
Use a first-order approximation of the exponential. This amounts to
7864
using an update rule of the type s <- s o (Id + u) instead of s <- s o
7869
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetUseGradientType "
7872
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::GetUseImageSpacing "
7875
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetIntensityDifferenceThreshold "
7877
Set/Get the threshold below which the absolute difference of intensity
7878
yields a match. When the intensities match between a moving and fixed
7879
image pixel, the update vector (for that iteration) will be the zero
7880
vector. Default is 0.001.
7884
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetMaximumError "
7886
Set/Get the desired maximum error of the Guassian kernel approximate.
7890
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetMaximumKernelWidth "
7892
Set/Get the desired limits of the Gaussian kernel width.
7896
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetMaximumRMSError "
7899
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetMaximumUpdateStepLength "
7901
Set/Get the maximum length in terms of pixels of the vectors in the
7906
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetNumberOfIterations "
7909
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetSmoothDisplacementField "
7911
Set/Get whether the displacement field is smoothed (regularized).
7912
Smoothing the displacement yields a solution elastic in nature. If
7913
SmoothDisplacementField is on, then the displacement field is smoothed
7914
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
7918
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetSmoothUpdateField "
7920
Set/Get whether the update field is smoothed (regularized). Smoothing
7921
the update field yields a solution viscous in nature. If
7922
SmoothUpdateField is on, then the update field is smoothed with a
7923
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
7927
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetStandardDeviations "
7929
Set/Get the Gaussian smoothing standard deviations for the
7930
displacement field. The values are set with respect to pixel
7935
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetStandardDeviations "
7937
Set the values of the StandardDeviations vector all to value
7941
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
7943
Set the Gaussian smoothing standard deviations for the update field.
7944
The values are set with respect to pixel coordinates.
7948
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
7950
Set the values of the UpdateFieldStandardDeviations vector all to
7955
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetUseFirstOrderExp "
7957
Use a first-order approximation of the exponential. This amounts to
7958
using an update rule of the type s <- s o (Id + u) instead of s <- s o
7963
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetUseGradientType "
7966
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SetUseImageSpacing "
7969
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SmoothDisplacementFieldOff "
7972
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SmoothDisplacementFieldOn "
7974
Set the value of SmoothDisplacementField to true or false
7979
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SmoothUpdateFieldOff "
7982
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::SmoothUpdateFieldOn "
7984
Set the value of SmoothUpdateField to true or false respectfully.
7988
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::ToString "
7994
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::UseFirstOrderExpOff "
7997
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::UseFirstOrderExpOn "
7999
Set the value of UseFirstOrderExp to true or false respectfully.
8003
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::UseImageSpacingOff "
8006
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::UseImageSpacingOn "
8008
Set the value of UseImageSpacing to true or false respectfully.
8012
%feature("docstring") itk::simple::DiffeomorphicDemonsRegistrationFilter::~DiffeomorphicDemonsRegistrationFilter "
8019
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter "
8021
dilation of an object in an image
8024
Dilate an image using binary morphology. Pixel values matching the
8025
object value are considered the \"foreground\" and all other pixels
8026
are \"background\". This is useful in processing mask images
8027
containing only one object.
8029
If a pixel's value is equal to the object value and the pixel is
8030
adjacent to a non-object valued pixel, then the kernel is centered on
8031
the object-value pixel and neighboring pixels covered by the kernel
8032
are assigned the object value. The structuring element is assumed to
8033
be composed of binary values (zero or one).
8037
ObjectMorphologyImageFilter , ErodeObjectMorphologyImageFilter
8039
BinaryDilateImageFilter
8041
itk::simple::DilateObjectMorphology for the procedural interface
8043
itk::DilateObjectMorphologyImageFilter for the Doxygen on the original ITK class.
8046
C++ includes: sitkDilateObjectMorphologyImageFilter.h
8049
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::DilateObjectMorphologyImageFilter "
8051
Default Constructor that takes no arguments and initializes default
8056
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::Execute "
8058
Execute the filter on the input image
8062
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::Execute "
8064
Execute the filter on the input image with the given parameters
8068
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::GetKernelRadius "
8071
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::GetKernelType "
8074
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::GetName "
8080
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::GetObjectValue "
8083
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::SetKernelRadius "
8085
Kernel radius as a scale for isotropic structures
8089
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::SetKernelRadius "
8091
Set/Get the radius of the kernel structuring element as a vector.
8093
If the dimension of the image is greater then the length of r, then
8094
the radius will be padded. If it is less the r will be truncated.
8098
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::SetKernelType "
8100
Set/Get the kernel or structuring elemenent used for the morphology
8104
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::SetKernelType "
8107
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::SetObjectValue "
8110
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::ToString "
8116
%feature("docstring") itk::simple::DilateObjectMorphologyImageFilter::~DilateObjectMorphologyImageFilter "
8123
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter "
8125
Calculates image derivatives using discrete derivative gaussian
8126
kernels. This filter calculates Gaussian derivative by separable
8127
convolution of an image and a discrete Gaussian derivative operator
8131
The Gaussian operators used here were described by Tony Lindeberg
8132
(Discrete Scale-Space Theory and the Scale-Space Primal Sketch.
8133
Dissertation. Royal Institute of Technology, Stockholm, Sweden. May
8136
The variance or standard deviation (sigma) will be evaluated as pixel
8137
units if SetUseImageSpacing is off (false) or as physical units if
8138
SetUseImageSpacing is on (true, default). The variance can be set
8139
independently in each dimension.
8141
When the Gaussian kernel is small, this filter tends to run faster
8142
than itk::RecursiveGaussianImageFilter .
8145
Ivan Macia, VICOMTech, Spain, http://www.vicomtech.es
8146
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/1290
8150
GaussianDerivativeOperator
8156
NeighborhoodOperator
8158
itk::simple::DiscreteGaussianDerivative for the procedural interface
8160
itk::DiscreteGaussianDerivativeImageFilter for the Doxygen on the original ITK class.
8163
C++ includes: sitkDiscreteGaussianDerivativeImageFilter.h
8166
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::DiscreteGaussianDerivativeImageFilter "
8168
Default Constructor that takes no arguments and initializes default
8173
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::Execute "
8175
Execute the filter on the input image
8179
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::Execute "
8181
Execute the filter on the input image with the given parameters
8185
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetMaximumError "
8187
The algorithm will size the discrete kernel so that the error
8188
resulting from truncation of the kernel is no greater than
8189
MaximumError. The default is 0.01 in each dimension.
8193
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetMaximumKernelWidth "
8195
Set the kernel to be no wider than MaximumKernelWidth pixels, even if
8196
MaximumError demands it. The default is 32 pixels.
8200
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetName "
8206
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetNormalizeAcrossScale "
8208
Set/Get the flag for calculating scale-space normalized derivatives.
8209
Normalized derivatives are obtained multiplying by the scale parameter
8214
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetOrder "
8216
Order of derivatives in each dimension. Sets the derivative order
8217
independently for each dimension, but see also SetOrder(const unsigned int v) . The default is 1 in each dimension.
8221
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetUseImageSpacing "
8223
Set/Get whether or not the filter will use the spacing of the input
8224
image in its calculations. Default is ImageSpacingOn.
8228
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::GetVariance "
8230
The variance for the discrete Gaussian kernel. Sets the variance
8231
independently for each dimension, but see also SetVariance(const double v) . The default is 0.0 in each dimension. If UseImageSpacing is true,
8232
the units are the physical units of your image. If UseImageSpacing is
8233
false then the units are pixels.
8237
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::NormalizeAcrossScaleOff "
8240
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::NormalizeAcrossScaleOn "
8242
Set the value of NormalizeAcrossScale to true or false respectfully.
8246
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetMaximumError "
8248
Convenience Set methods for setting all dimensional parameters to the
8253
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetMaximumKernelWidth "
8255
Set the kernel to be no wider than MaximumKernelWidth pixels, even if
8256
MaximumError demands it. The default is 32 pixels.
8260
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetNormalizeAcrossScale "
8262
Set/Get the flag for calculating scale-space normalized derivatives.
8263
Normalized derivatives are obtained multiplying by the scale parameter
8268
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetOrder "
8270
Convenience Set methods for setting all dimensional parameters to the
8275
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetOrder "
8277
Set the values of the Order vector all to value
8281
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetUseImageSpacing "
8283
Set/Get whether or not the filter will use the spacing of the input
8284
image in its calculations. Default is ImageSpacingOn.
8288
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetVariance "
8290
Convenience Set methods for setting all dimensional parameters to the
8295
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::SetVariance "
8297
Set the values of the Variance vector all to value
8301
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::ToString "
8307
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::UseImageSpacingOff "
8310
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::UseImageSpacingOn "
8312
Set the value of UseImageSpacing to true or false respectfully.
8316
%feature("docstring") itk::simple::DiscreteGaussianDerivativeImageFilter::~DiscreteGaussianDerivativeImageFilter "
8323
%feature("docstring") itk::simple::DiscreteGaussianImageFilter "
8325
Blurs an image by separable convolution with discrete gaussian
8326
kernels. This filter performs Gaussian blurring by separable
8327
convolution of an image and a discrete Gaussian operator (kernel).
8330
The Gaussian operator used here was described by Tony Lindeberg
8331
(Discrete Scale-Space Theory and the Scale-Space Primal Sketch.
8332
Dissertation. Royal Institute of Technology, Stockholm, Sweden. May
8333
1991.) The Gaussian kernel used here was designed so that smoothing
8334
and derivative operations commute after discretization.
8336
The variance or standard deviation (sigma) will be evaluated as pixel
8337
units if SetUseImageSpacing is off (false) or as physical units if
8338
SetUseImageSpacing is on (true, default). The variance can be set
8339
independently in each dimension.
8341
When the Gaussian kernel is small, this filter tends to run faster
8342
than itk::RecursiveGaussianImageFilter .
8352
NeighborhoodOperator
8354
RecursiveGaussianImageFilter
8359
Smooth an image with a discrete Gaussian filter
8361
itk::simple::DiscreteGaussian for the procedural interface
8363
itk::DiscreteGaussianImageFilter for the Doxygen on the original ITK class.
8367
C++ includes: sitkDiscreteGaussianImageFilter.h
8370
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::DiscreteGaussianImageFilter "
8372
Default Constructor that takes no arguments and initializes default
8377
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::Execute "
8379
Execute the filter on the input image
8383
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::Execute "
8385
Execute the filter on the input image with the given parameters
8389
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::GetMaximumError "
8391
The algorithm will size the discrete kernel so that the error
8392
resulting from truncation of the kernel is no greater than
8393
MaximumError. The default is 0.01 in each dimension.
8397
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::GetMaximumKernelWidth "
8399
Set the kernel to be no wider than MaximumKernelWidth pixels, even if
8400
MaximumError demands it. The default is 32 pixels.
8404
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::GetName "
8410
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::GetUseImageSpacing "
8412
Set/Get whether or not the filter will use the spacing of the input
8413
image in its calculations
8417
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::GetVariance "
8419
The variance for the discrete Gaussian kernel. Sets the variance
8420
independently for each dimension, but see also SetVariance(const double v) . The default is 0.0 in each dimension. If UseImageSpacing is true,
8421
the units are the physical units of your image. If UseImageSpacing is
8422
false then the units are pixels.
8426
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::SetMaximumError "
8429
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::SetMaximumKernelWidth "
8431
Set the kernel to be no wider than MaximumKernelWidth pixels, even if
8432
MaximumError demands it. The default is 32 pixels.
8436
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::SetUseImageSpacing "
8438
Set/Get whether or not the filter will use the spacing of the input
8439
image in its calculations
8443
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::SetVariance "
8446
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::ToString "
8452
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::UseImageSpacingOff "
8455
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::UseImageSpacingOn "
8457
Set the value of UseImageSpacing to true or false respectfully.
8461
%feature("docstring") itk::simple::DiscreteGaussianImageFilter::~DiscreteGaussianImageFilter "
8468
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter "
8470
Computes a scalar image from a vector image (e.g., deformation field)
8471
input, where each output scalar at each pixel is the Jacobian
8472
determinant of the vector field at that location. This calculation is
8473
correct in the case where the vector image is a \"displacement\" from
8474
the current location. The computation for the jacobian determinant is:
8475
det[ dT/dx ] = det[ I + du/dx ].
8479
This filter is based on itkVectorGradientMagnitudeImageFilter and
8480
supports the m_DerivativeWeights weights for partial derivatives.
8481
Note that the determinant of a zero vector field is also zero,
8482
whereas the Jacobian determinant of the corresponding identity warp
8483
transformation is 1.0. In order to compute the effective deformation
8484
Jacobian determinant 1.0 must be added to the diagonal elements of
8485
Jacobian prior to taking the derivative. i.e. det([ (1.0+dx/dx) dx/dy
8486
dx/dz ; dy/dx (1.0+dy/dy) dy/dz; dz/dx dz/dy (1.0+dz/dz) ])
8488
Template Parameters (Input and Output)
8489
This filter has one required template parameter which defines the
8490
input image type. The pixel type of the input image is assumed to be a
8491
vector (e.g., itk::Vector , itk::RGBPixel , itk::FixedArray ). The scalar type of the vector components must be castable to
8492
floating point. Instantiating with an image of RGBPixel<unsigned
8493
short>, for example, is allowed, but the filter will convert it to an
8494
image of Vector<float,3> for processing.
8495
The second template parameter, TRealType, can be optionally specified
8496
to define the scalar numerical type used in calculations. This is the
8497
component type of the output image, which will be of
8498
itk::Vector<TRealType, N>, where N is the number of channels in the
8499
multiple component input image. The default type of TRealType is
8500
float. For extra precision, you may safely change this parameter to
8503
The third template parameter is the output image type. The third
8504
parameter will be automatically constructed from the first and second
8505
parameters, so it is not necessary (or advisable) to set this
8506
parameter explicitly. Given an M-channel input image with
8507
dimensionality N, and a numerical type specified as TRealType, the
8508
output image will be of type itk::Image<TRealType, N>.
8511
The method SetUseImageSpacingOn will cause derivatives in the image to
8512
be scaled (inversely) with the pixel size of the input image,
8513
effectively taking derivatives in world coordinates (versus isotropic
8514
image space). SetUseImageSpacingOff turns this functionality off.
8515
Default is UseImageSpacingOn. The parameter UseImageSpacing can be set
8516
directly with the method SetUseImageSpacing(bool) .
8517
Weights can be applied to the derivatives directly using the
8518
SetDerivativeWeights method. Note that if UseImageSpacing is set to
8519
TRUE (ON), then these weights will be overridden by weights derived
8520
from the image spacing when the filter is updated. The argument to
8521
this method is a C array of TRealValue type.
8524
We use vnl_det for determinent computation, which only supports square
8525
matrices. So the vector dimension of the input image values must be
8526
equal to the image dimensions, which is trivially true for a
8527
deformation field that maps an n-dimensional space onto itself.
8528
Currently, dimensions up to and including 4 are supported. This
8529
limitation comes from the presence of vnl_det() functions for matrices
8530
of dimension up to 4x4.
8532
The template parameter TRealType must be floating point (float or
8533
double) or a user-defined \"real\" numerical type with arithmetic
8534
operations defined sufficient to compute derivatives.
8542
NeighborhoodOperator
8544
NeighborhoodIterator
8546
This class was adapted by
8548
Hans J. Johnson, The University of Iowa from code provided by
8549
Tom Vercauteren, INRIA & Mauna Kea Technologies
8551
Torsten Rohlfing, Neuroscience Program, SRI International.
8553
itk::simple::DisplacementFieldJacobianDeterminantFilter for the procedural interface
8555
itk::DisplacementFieldJacobianDeterminantFilter for the Doxygen on the original ITK class.
8558
C++ includes: sitkDisplacementFieldJacobianDeterminantFilter.h
8561
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::DisplacementFieldJacobianDeterminantFilter "
8563
Default Constructor that takes no arguments and initializes default
8568
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::Execute "
8570
Execute the filter on the input image
8574
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::Execute "
8576
Execute the filter on the input image with the given parameters
8580
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::GetDerivativeWeights "
8582
Directly Set/Get the array of weights used in the gradient
8583
calculations. Note that calling UseImageSpacingOn will clobber these
8588
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::GetName "
8594
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::GetUseImageSpacing "
8597
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::SetDerivativeWeights "
8599
Directly Set/Get the array of weights used in the gradient
8600
calculations. Note that calling UseImageSpacingOn will clobber these
8605
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::SetUseImageSpacing "
8607
Set/Get whether or not the filter will use the spacing of the input
8608
image in its calculations
8612
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::ToString "
8618
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::UseImageSpacingOff "
8621
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::UseImageSpacingOn "
8623
Set the value of UseImageSpacing to true or false respectfully.
8627
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminantFilter::~DisplacementFieldJacobianDeterminantFilter "
8634
%feature("docstring") itk::simple::DisplacementFieldTransform "
8636
A dense deformable transform over a bounded spatial domain for 2D or
8637
3D coordinates space.
8642
itk::DisplacementFieldTransform
8645
C++ includes: sitkDisplacementFieldTransform.h
8648
%feature("docstring") itk::simple::DisplacementFieldTransform::DisplacementFieldTransform "
8651
%feature("docstring") itk::simple::DisplacementFieldTransform::DisplacementFieldTransform "
8653
Consume an image to construct a displacement field transform.
8658
The input displacement image is transferred to the constructed
8659
transform object. The input image is modified to be a default
8660
constructed Image object.
8661
Image must be of sitkVectorFloat64 pixel type with the number of components
8662
equal to the image dimension.
8666
%feature("docstring") itk::simple::DisplacementFieldTransform::DisplacementFieldTransform "
8669
%feature("docstring") itk::simple::DisplacementFieldTransform::DisplacementFieldTransform "
8672
%feature("docstring") itk::simple::DisplacementFieldTransform::GetDisplacementField "
8675
The returned image should not directly modify the internal
8681
%feature("docstring") itk::simple::DisplacementFieldTransform::GetInverseDisplacementField "
8684
The returned image is should not directly modify the internal
8690
%feature("docstring") itk::simple::DisplacementFieldTransform::GetName "
8696
%feature("docstring") itk::simple::DisplacementFieldTransform::SetDisplacementField "
8698
Consume an image, and set the displacement field.
8703
The ownership of the input displacement image is transferred to the
8704
constructed transform object. The input image is modified to be a
8705
default constructed Image object.
8706
Image must be of sitkVectorFloat64 pixel type with the number of components
8707
equal to the image dimension.
8711
%feature("docstring") itk::simple::DisplacementFieldTransform::SetInterpolator "
8713
Set the interpolator used between the field voxels.
8717
%feature("docstring") itk::simple::DisplacementFieldTransform::SetInverseDisplacementField "
8723
%feature("docstring") itk::simple::DisplacementFieldTransform::SetSmoothingBSplineOnUpdate "
8726
%feature("docstring") itk::simple::DisplacementFieldTransform::SetSmoothingGaussianOnUpdate "
8729
%feature("docstring") itk::simple::DisplacementFieldTransform::SetSmoothingOff "
8733
%feature("docstring") itk::simple::DivideFloorImageFilter "
8735
Implements pixel-wise generic operation of two images, or of an image
8739
This class is parameterized over the types of the two input images and
8740
the type of the output image. It is also parameterized by the
8741
operation to be applied. A Functor style is used.
8743
The constant must be of the same type than the pixel type of the
8744
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
8745
GetConstant() methods are provided as shortcuts to set or get the
8746
constant value without manipulating the decorator.
8750
UnaryFunctorImageFilter TernaryFunctorImageFilter
8755
Apply a predefined operation to corresponding pixels in two images
8757
Apply a custom operation to corresponding pixels in two images
8759
itk::simple::DivideFloor for the procedural interface
8761
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
8765
C++ includes: sitkDivideFloorImageFilter.h
8768
%feature("docstring") itk::simple::DivideFloorImageFilter::DivideFloorImageFilter "
8770
Default Constructor that takes no arguments and initializes default
8775
%feature("docstring") itk::simple::DivideFloorImageFilter::Execute "
8777
Execute the filter on the input images
8781
%feature("docstring") itk::simple::DivideFloorImageFilter::Execute "
8783
Execute the filter with an image and a constant
8787
%feature("docstring") itk::simple::DivideFloorImageFilter::Execute "
8790
%feature("docstring") itk::simple::DivideFloorImageFilter::GetName "
8796
%feature("docstring") itk::simple::DivideFloorImageFilter::ToString "
8802
%feature("docstring") itk::simple::DivideFloorImageFilter::~DivideFloorImageFilter "
8809
%feature("docstring") itk::simple::DivideImageFilter "
8811
Pixel-wise division of two images.
8814
This class is templated over the types of the two input images and the
8815
type of the output image. When the divisor is zero, the division
8816
result is set to the maximum number that can be represented by default
8817
to avoid exception. Numeric conversions (castings) are done by the C++
8824
Pixel-wise division of two images
8826
itk::simple::Divide for the procedural interface
8828
itk::DivideImageFilter for the Doxygen on the original ITK class.
8832
C++ includes: sitkDivideImageFilter.h
8835
%feature("docstring") itk::simple::DivideImageFilter::DivideImageFilter "
8837
Default Constructor that takes no arguments and initializes default
8842
%feature("docstring") itk::simple::DivideImageFilter::Execute "
8844
Execute the filter on the input images
8848
%feature("docstring") itk::simple::DivideImageFilter::Execute "
8850
Execute the filter with an image and a constant
8854
%feature("docstring") itk::simple::DivideImageFilter::Execute "
8857
%feature("docstring") itk::simple::DivideImageFilter::GetName "
8863
%feature("docstring") itk::simple::DivideImageFilter::ToString "
8869
%feature("docstring") itk::simple::DivideImageFilter::~DivideImageFilter "
8876
%feature("docstring") itk::simple::DivideRealImageFilter "
8878
Implements pixel-wise generic operation of two images, or of an image
8882
This class is parameterized over the types of the two input images and
8883
the type of the output image. It is also parameterized by the
8884
operation to be applied. A Functor style is used.
8886
The constant must be of the same type than the pixel type of the
8887
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
8888
GetConstant() methods are provided as shortcuts to set or get the
8889
constant value without manipulating the decorator.
8893
UnaryFunctorImageFilter TernaryFunctorImageFilter
8898
Apply a predefined operation to corresponding pixels in two images
8900
Apply a custom operation to corresponding pixels in two images
8902
itk::simple::DivideReal for the procedural interface
8904
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
8908
C++ includes: sitkDivideRealImageFilter.h
8911
%feature("docstring") itk::simple::DivideRealImageFilter::DivideRealImageFilter "
8913
Default Constructor that takes no arguments and initializes default
8918
%feature("docstring") itk::simple::DivideRealImageFilter::Execute "
8920
Execute the filter on the input images
8924
%feature("docstring") itk::simple::DivideRealImageFilter::Execute "
8926
Execute the filter with an image and a constant
8930
%feature("docstring") itk::simple::DivideRealImageFilter::Execute "
8933
%feature("docstring") itk::simple::DivideRealImageFilter::GetName "
8939
%feature("docstring") itk::simple::DivideRealImageFilter::ToString "
8945
%feature("docstring") itk::simple::DivideRealImageFilter::~DivideRealImageFilter "
8952
%feature("docstring") itk::simple::DoubleThresholdImageFilter "
8954
Binarize an input image using double thresholding.
8957
Double threshold addresses the difficulty in selecting a threshold
8958
that will select the objects of interest without selecting extraneous
8959
objects. Double threshold considers two threshold ranges: a narrow
8960
range and a wide range (where the wide range encompasses the narrow
8961
range). If the wide range was used for a traditional threshold (where
8962
values inside the range map to the foreground and values outside the
8963
range map to the background), many extraneous pixels may survive the
8964
threshold operation. If the narrow range was used for a traditional
8965
threshold, then too few pixels may survive the threshold.
8967
Double threshold uses the narrow threshold image as a marker image and
8968
the wide threshold image as a mask image in the geodesic dilation.
8969
Essentially, the marker image (narrow threshold) is dilated but
8970
constrained to lie within the mask image (wide threshold). Thus, only
8971
the objects of interest (those pixels that survived the narrow
8972
threshold) are extracted but the those objects appear in the final
8973
image as they would have if the wide threshold was used.
8977
GrayscaleGeodesicDilateImageFilter
8979
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
8981
itk::simple::DoubleThreshold for the procedural interface
8983
itk::DoubleThresholdImageFilter for the Doxygen on the original ITK class.
8986
C++ includes: sitkDoubleThresholdImageFilter.h
8989
%feature("docstring") itk::simple::DoubleThresholdImageFilter::DoubleThresholdImageFilter "
8991
Default Constructor that takes no arguments and initializes default
8996
%feature("docstring") itk::simple::DoubleThresholdImageFilter::Execute "
8998
Execute the filter on the input image
9002
%feature("docstring") itk::simple::DoubleThresholdImageFilter::Execute "
9004
Execute the filter on the input image with the given parameters
9008
%feature("docstring") itk::simple::DoubleThresholdImageFilter::FullyConnectedOff "
9011
%feature("docstring") itk::simple::DoubleThresholdImageFilter::FullyConnectedOn "
9013
Set the value of FullyConnected to true or false respectfully.
9017
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetFullyConnected "
9019
Set/Get whether the connected components are defined strictly by face
9020
connectivity or by face+edge+vertex connectivity. Default is
9021
FullyConnectedOff. For objects that are 1 pixel wide, use
9026
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetInsideValue "
9028
Get the \"inside\" pixel value.
9032
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetName "
9038
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetOutsideValue "
9040
Get the \"outside\" pixel value.
9044
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetThreshold1 "
9046
Get the threshold values.
9050
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetThreshold2 "
9052
Get the threshold values.
9056
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetThreshold3 "
9058
Get the threshold values.
9062
%feature("docstring") itk::simple::DoubleThresholdImageFilter::GetThreshold4 "
9064
Get the threshold values.
9068
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetFullyConnected "
9070
Set/Get whether the connected components are defined strictly by face
9071
connectivity or by face+edge+vertex connectivity. Default is
9072
FullyConnectedOff. For objects that are 1 pixel wide, use
9077
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetInsideValue "
9079
Set the \"inside\" pixel value. The default value NumericTraits<OutputPixelType>::max()
9083
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetOutsideValue "
9085
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::ZeroValue() .
9089
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetThreshold1 "
9091
Set the thresholds. Four thresholds should be specified. The two lower
9092
thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.
9096
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetThreshold2 "
9098
Set the thresholds. Four thresholds should be specified. The two lower
9099
thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.
9103
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetThreshold3 "
9105
Set the thresholds. Four thresholds should be specified. The two lower
9106
thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.
9110
%feature("docstring") itk::simple::DoubleThresholdImageFilter::SetThreshold4 "
9112
Set the thresholds. Four thresholds should be specified. The two lower
9113
thresholds default to NumericTraits<InputPixelType>::NonpositiveMin() . The two upper thresholds default NumericTraits<InputPixelType>::max . Threshold1 <= Threshold2 <= Threshold3 <= Threshold4.
9117
%feature("docstring") itk::simple::DoubleThresholdImageFilter::ToString "
9123
%feature("docstring") itk::simple::DoubleThresholdImageFilter::~DoubleThresholdImageFilter "
9130
%feature("docstring") itk::simple::EdgePotentialImageFilter "
9132
Computes the edge potential of an image from the image gradient.
9135
Input to this filter should be a CovariantVector image representing the image gradient.
9137
The filter expect both the input and output images to have the same
9138
number of dimensions, and the output to be of a scalar image type.
9140
itk::simple::EdgePotential for the procedural interface
9142
itk::EdgePotentialImageFilter for the Doxygen on the original ITK class.
9145
C++ includes: sitkEdgePotentialImageFilter.h
9148
%feature("docstring") itk::simple::EdgePotentialImageFilter::EdgePotentialImageFilter "
9150
Default Constructor that takes no arguments and initializes default
9155
%feature("docstring") itk::simple::EdgePotentialImageFilter::Execute "
9157
Execute the filter on the input image
9161
%feature("docstring") itk::simple::EdgePotentialImageFilter::GetName "
9167
%feature("docstring") itk::simple::EdgePotentialImageFilter::ToString "
9173
%feature("docstring") itk::simple::EdgePotentialImageFilter::~EdgePotentialImageFilter "
9180
%feature("docstring") itk::simple::EqualImageFilter "
9182
Implements pixel-wise generic operation of two images, or of an image
9186
This class is parameterized over the types of the two input images and
9187
the type of the output image. It is also parameterized by the
9188
operation to be applied. A Functor style is used.
9190
The constant must be of the same type than the pixel type of the
9191
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
9192
GetConstant() methods are provided as shortcuts to set or get the
9193
constant value without manipulating the decorator.
9197
UnaryFunctorImageFilter TernaryFunctorImageFilter
9202
Apply a predefined operation to corresponding pixels in two images
9204
Apply a custom operation to corresponding pixels in two images
9206
itk::simple::Equal for the procedural interface
9208
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
9212
C++ includes: sitkEqualImageFilter.h
9215
%feature("docstring") itk::simple::EqualImageFilter::EqualImageFilter "
9217
Default Constructor that takes no arguments and initializes default
9222
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9224
Execute the filter on the input images
9228
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9230
Execute the filter on the input images with the given parameters
9234
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9236
Execute the filter with an image and a constant
9240
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9243
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9245
Execute the filter on an image and a constant with the given
9250
%feature("docstring") itk::simple::EqualImageFilter::Execute "
9253
%feature("docstring") itk::simple::EqualImageFilter::GetBackgroundValue "
9255
Set/Get the value used to mark the false pixels of the operator.
9259
%feature("docstring") itk::simple::EqualImageFilter::GetForegroundValue "
9261
Set/Get the value used to mark the true pixels of the operator.
9265
%feature("docstring") itk::simple::EqualImageFilter::GetName "
9271
%feature("docstring") itk::simple::EqualImageFilter::SetBackgroundValue "
9273
Set/Get the value used to mark the false pixels of the operator.
9277
%feature("docstring") itk::simple::EqualImageFilter::SetForegroundValue "
9279
Set/Get the value used to mark the true pixels of the operator.
9283
%feature("docstring") itk::simple::EqualImageFilter::ToString "
9289
%feature("docstring") itk::simple::EqualImageFilter::~EqualImageFilter "
9296
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter "
9298
Erosion of an object in an image.
9301
Erosion of an image using binary morphology. Pixel values matching the
9302
object value are considered the \"object\" and all other pixels are
9303
\"background\". This is useful in processing mask images containing
9306
If the pixel covered by the center of the kernel has the pixel value
9307
ObjectValue and the pixel is adjacent to a non-object valued pixel,
9308
then the kernel is centered on the object-value pixel and neighboring
9309
pixels covered by the kernel are assigned the background value. The
9310
structuring element is assumed to be composed of binary values (zero
9315
ObjectMorphologyImageFilter , BinaryFunctionErodeImageFilter
9317
BinaryErodeImageFilter
9319
itk::simple::ErodeObjectMorphology for the procedural interface
9321
itk::ErodeObjectMorphologyImageFilter for the Doxygen on the original ITK class.
9324
C++ includes: sitkErodeObjectMorphologyImageFilter.h
9327
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::ErodeObjectMorphologyImageFilter "
9329
Default Constructor that takes no arguments and initializes default
9334
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::Execute "
9336
Execute the filter on the input image
9340
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::Execute "
9342
Execute the filter on the input image with the given parameters
9346
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::GetBackgroundValue "
9348
Get the value to be assigned to eroded pixels
9352
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::GetKernelRadius "
9355
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::GetKernelType "
9358
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::GetName "
9364
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::GetObjectValue "
9367
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetBackgroundValue "
9369
Set the value to be assigned to eroded pixels
9373
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetKernelRadius "
9375
Kernel radius as a scale for isotropic structures
9379
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetKernelRadius "
9381
Set/Get the radius of the kernel structuring element as a vector.
9383
If the dimension of the image is greater then the length of r, then
9384
the radius will be padded. If it is less the r will be truncated.
9388
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetKernelType "
9390
Set/Get the kernel or structuring elemenent used for the morphology
9394
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetKernelType "
9397
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::SetObjectValue "
9400
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::ToString "
9406
%feature("docstring") itk::simple::ErodeObjectMorphologyImageFilter::~ErodeObjectMorphologyImageFilter "
9413
%feature("docstring") itk::simple::Euler2DTransform "
9415
A rigid 2D transform with rotation in radians around a fixed center
9421
itk::Euler2DTransform
9424
C++ includes: sitkEuler2DTransform.h
9427
%feature("docstring") itk::simple::Euler2DTransform::Euler2DTransform "
9430
%feature("docstring") itk::simple::Euler2DTransform::Euler2DTransform "
9433
%feature("docstring") itk::simple::Euler2DTransform::Euler2DTransform "
9436
%feature("docstring") itk::simple::Euler2DTransform::Euler2DTransform "
9439
%feature("docstring") itk::simple::Euler2DTransform::GetAngle "
9442
%feature("docstring") itk::simple::Euler2DTransform::GetCenter "
9445
%feature("docstring") itk::simple::Euler2DTransform::GetMatrix "
9451
%feature("docstring") itk::simple::Euler2DTransform::GetName "
9457
%feature("docstring") itk::simple::Euler2DTransform::GetTranslation "
9460
%feature("docstring") itk::simple::Euler2DTransform::SetAngle "
9466
%feature("docstring") itk::simple::Euler2DTransform::SetCenter "
9472
%feature("docstring") itk::simple::Euler2DTransform::SetMatrix "
9475
%feature("docstring") itk::simple::Euler2DTransform::SetTranslation "
9479
%feature("docstring") itk::simple::Euler3DTransform "
9481
A rigid 3D transform with rotation in radians around a fixed center
9487
itk::Euler3DTransform
9490
C++ includes: sitkEuler3DTransform.h
9493
%feature("docstring") itk::simple::Euler3DTransform::ComputeZYXOff "
9496
%feature("docstring") itk::simple::Euler3DTransform::ComputeZYXOn "
9499
%feature("docstring") itk::simple::Euler3DTransform::Euler3DTransform "
9502
%feature("docstring") itk::simple::Euler3DTransform::Euler3DTransform "
9505
%feature("docstring") itk::simple::Euler3DTransform::Euler3DTransform "
9508
%feature("docstring") itk::simple::Euler3DTransform::Euler3DTransform "
9511
%feature("docstring") itk::simple::Euler3DTransform::GetAngleX "
9514
%feature("docstring") itk::simple::Euler3DTransform::GetAngleY "
9517
%feature("docstring") itk::simple::Euler3DTransform::GetAngleZ "
9520
%feature("docstring") itk::simple::Euler3DTransform::GetCenter "
9523
%feature("docstring") itk::simple::Euler3DTransform::GetComputeZYX "
9526
%feature("docstring") itk::simple::Euler3DTransform::GetMatrix "
9532
%feature("docstring") itk::simple::Euler3DTransform::GetName "
9538
%feature("docstring") itk::simple::Euler3DTransform::GetTranslation "
9541
%feature("docstring") itk::simple::Euler3DTransform::SetCenter "
9547
%feature("docstring") itk::simple::Euler3DTransform::SetComputeZYX "
9550
%feature("docstring") itk::simple::Euler3DTransform::SetMatrix "
9553
%feature("docstring") itk::simple::Euler3DTransform::SetRotation "
9559
%feature("docstring") itk::simple::Euler3DTransform::SetTranslation "
9563
%feature("docstring") itk::simple::ExpImageFilter "
9565
Computes the exponential function of each pixel.
9568
The computation is performed using std::exp(x).
9570
itk::simple::Exp for the procedural interface
9572
itk::ExpImageFilter for the Doxygen on the original ITK class.
9575
C++ includes: sitkExpImageFilter.h
9578
%feature("docstring") itk::simple::ExpImageFilter::Execute "
9580
Execute the filter on the input image
9584
%feature("docstring") itk::simple::ExpImageFilter::ExpImageFilter "
9586
Default Constructor that takes no arguments and initializes default
9591
%feature("docstring") itk::simple::ExpImageFilter::GetName "
9597
%feature("docstring") itk::simple::ExpImageFilter::ToString "
9603
%feature("docstring") itk::simple::ExpImageFilter::~ExpImageFilter "
9610
%feature("docstring") itk::simple::ExpNegativeImageFilter "
9612
Computes the function exp(-K.x) for each input pixel.
9615
Every output pixel is equal to std::exp(-K.x ). where x is the
9616
intensity of the homologous input pixel, and K is a user-provided
9619
itk::simple::ExpNegative for the procedural interface
9621
itk::ExpNegativeImageFilter for the Doxygen on the original ITK class.
9624
C++ includes: sitkExpNegativeImageFilter.h
9627
%feature("docstring") itk::simple::ExpNegativeImageFilter::Execute "
9629
Execute the filter on the input image
9633
%feature("docstring") itk::simple::ExpNegativeImageFilter::ExpNegativeImageFilter "
9635
Default Constructor that takes no arguments and initializes default
9640
%feature("docstring") itk::simple::ExpNegativeImageFilter::GetName "
9646
%feature("docstring") itk::simple::ExpNegativeImageFilter::ToString "
9652
%feature("docstring") itk::simple::ExpNegativeImageFilter::~ExpNegativeImageFilter "
9659
%feature("docstring") itk::simple::ExpandImageFilter "
9661
Expand the size of an image by an integer factor in each dimension.
9664
ExpandImageFilter increases the size of an image by an integer factor in each dimension
9665
using a interpolation method. The output image size in each dimension
9668
OutputSize[j] = InputSize[j] * ExpandFactors[j]
9670
The output values are obtained by interpolating the input image. The
9671
default interpolation type used is the LinearInterpolateImageFunction . The user can specify a particular interpolation function via SetInterpolator() . Note that the input interpolator must derive from base class InterpolateImageFunction .
9673
This filter will produce an output with different pixel spacing that
9674
its input image such that:
9676
OutputSpacing[j] = InputSpacing[j] / ExpandFactors[j]
9678
The filter is templated over the input image type and the output image
9681
This filter is implemented as a multithreaded filter and supports
9686
This filter only works for image with scalar pixel types. For vector
9687
images use VectorExpandImageFilter .
9688
This filter assumes that the input and output image has the same
9689
number of dimensions.
9693
InterpolateImageFunction
9695
LinearInterpolationImageFunction
9697
VectorExpandImageFilter
9699
itk::simple::Expand for the procedural interface
9701
itk::ExpandImageFilter for the Doxygen on the original ITK class.
9704
C++ includes: sitkExpandImageFilter.h
9707
%feature("docstring") itk::simple::ExpandImageFilter::Execute "
9709
Execute the filter on the input image
9713
%feature("docstring") itk::simple::ExpandImageFilter::Execute "
9715
Execute the filter on the input image with the given parameters
9719
%feature("docstring") itk::simple::ExpandImageFilter::ExpandImageFilter "
9721
Default Constructor that takes no arguments and initializes default
9726
%feature("docstring") itk::simple::ExpandImageFilter::GetExpandFactors "
9728
Get the expand factors.
9732
%feature("docstring") itk::simple::ExpandImageFilter::GetInterpolator "
9734
Get/Set the interpolator function.
9738
%feature("docstring") itk::simple::ExpandImageFilter::GetName "
9744
%feature("docstring") itk::simple::ExpandImageFilter::SetExpandFactor "
9746
Custom public declarations
9750
%feature("docstring") itk::simple::ExpandImageFilter::SetExpandFactors "
9752
Set the expand factors. Values are clamped to a minimum value of 1.
9753
Default is 1 for all dimensions.
9757
%feature("docstring") itk::simple::ExpandImageFilter::SetExpandFactors "
9759
Set the values of the ExpandFactors vector all to value
9763
%feature("docstring") itk::simple::ExpandImageFilter::SetInterpolator "
9765
Get/Set the interpolator function.
9769
%feature("docstring") itk::simple::ExpandImageFilter::ToString "
9775
%feature("docstring") itk::simple::ExpandImageFilter::~ExpandImageFilter "
9782
%feature("docstring") itk::simple::ExtractImageFilter "
9784
Decrease the image size by cropping the image to the selected region
9788
ExtractImageFilter changes the image boundary of an image by removing pixels outside the
9789
target region. The target region must be specified.
9791
ExtractImageFilter also collapses dimensions so that the input image may have more
9792
dimensions than the output image (i.e. 4-D input image to a 3-D output
9793
image). To specify what dimensions to collapse, the ExtractionRegion
9794
must be specified. For any dimension dim where
9795
ExtractionRegion.Size[dim] = 0, that dimension is collapsed. The index
9796
to collapse on is specified by ExtractionRegion.Index[dim]. For
9797
example, we have a image 4D = a 4x4x4x4 image, and we want to get a 3D
9798
image, 3D = a 4x4x4 image, specified as [x,y,z,2] from 4D (i.e. the
9799
3rd \"time\" slice from 4D). The ExtractionRegion.Size = [4,4,4,0] and
9800
ExtractionRegion.Index = [0,0,0,2].
9802
The number of dimension in ExtractionRegion.Size and Index must = InputImageDimension. The number of non-zero dimensions in
9803
ExtractionRegion.Size must = OutputImageDimension.
9805
The output image produced by this filter will have the same origin as
9806
the input image, while the ImageRegion of the output image will start at the starting index value provided
9807
in the ExtractRegion parameter. If you are looking for a filter that
9808
will re-compute the origin of the output image, and provide an output
9809
image region whose index is set to zeros, then you may want to use the RegionOfInterestImageFilter . The output spacing is is simply the collapsed version of the input
9812
Determining the direction of the collapsed output image from an larger
9813
dimensional input space is an ill defined problem in general. It is
9814
required that the application developer select the desired
9815
transformation strategy for collapsing direction cosines. It is
9816
REQUIRED that a strategy be explicitly requested (i.e. there is no
9817
working default). Direction Collapsing Strategies: 1)
9818
DirectionCollapseToUnknown(); This is the default and the filter can
9819
not run when this is set. The reason is to explicitly force the
9820
application developer to define their desired behavior. 1)
9821
DirectionCollapseToIdentity(); Output has identity direction no matter
9822
what 2) DirectionCollapseToSubmatrix(); Output direction is the sub-
9823
matrix if it is positive definite, else throw an exception.
9825
This filter is implemented as a multithreaded filter. It provides a
9826
ThreadedGenerateData() method for its implementation.
9829
This filter is derived from InPlaceImageFilter . When the input to this filter matched the output requirested
9830
region, like with streaming filter for input, then setting this filter
9831
to run in-place will result in no copying of the bulk pixel data.
9839
Crop an image by specifying the region to keep
9841
itk::simple::Extract for the procedural interface
9843
itk::ExtractImageFilter<InputImageType, typename InputImageType::template Rebind for the
9844
Doxygen on the original ITK class.
9848
C++ includes: sitkExtractImageFilter.h
9851
%feature("docstring") itk::simple::ExtractImageFilter::Execute "
9853
Execute the filter on the input image
9857
%feature("docstring") itk::simple::ExtractImageFilter::Execute "
9859
Execute the filter on the input image with the given parameters
9863
%feature("docstring") itk::simple::ExtractImageFilter::ExtractImageFilter "
9865
Default Constructor that takes no arguments and initializes default
9870
%feature("docstring") itk::simple::ExtractImageFilter::GetDirectionCollapseToStrategy "
9872
NOTE: The SetDirectionCollapseToUknown is explicitly not defined. It
9873
is a state that a filter can be in only when it is first instantiate
9874
prior to being initialized. Get the currently set strategy for
9875
collapsing directions of physical space.
9879
%feature("docstring") itk::simple::ExtractImageFilter::GetIndex "
9882
%feature("docstring") itk::simple::ExtractImageFilter::GetName "
9888
%feature("docstring") itk::simple::ExtractImageFilter::GetSize "
9891
%feature("docstring") itk::simple::ExtractImageFilter::SetDirectionCollapseToStrategy "
9893
Set the strategy to be used to collapse physical space
9896
itk::itkExtractImageFilter::DIRECTIONCOLLAPSETOIDENTITY Set the
9897
strategy so that all collapsed images have an identity direction. Use
9898
this strategy when you know that retention of the physical space
9899
orientation of the collapsed image is not important.
9901
itk::itkExtractImageFilter::DIRECTIONCOLLAPSETOGUESS Set the strategy
9902
so that all collapsed images where output direction is the sub-matrix
9903
if it is positive definite, else return identity. This is backwards
9904
compatible with ITKv3, but is highly discouraged because the results
9905
are difficult to anticipate under differing data scenerios.
9907
itk::itkExtractImageFilter::DIRECTIONCOLLAPSETOSUBMATRIX Set the
9908
strategy so that all collapsed images where output direction is the
9909
sub-matrix if it is positive definite, else throw an exception. Use
9910
this strategy when it is known that properly identified physical space
9911
sub-volumes can be reliably extracted from a higher dimensional space.
9912
For example when the application programmer knows that a 4D image is
9913
3D+time, and that the 3D sub-space is properly defined.
9917
%feature("docstring") itk::simple::ExtractImageFilter::SetIndex "
9919
odo the internal setting of the method needs work!!!
9923
%feature("docstring") itk::simple::ExtractImageFilter::SetSize "
9926
%feature("docstring") itk::simple::ExtractImageFilter::ToString "
9932
%feature("docstring") itk::simple::ExtractImageFilter::~ExtractImageFilter "
9939
%feature("docstring") itk::simple::FFTConvolutionImageFilter "
9941
Convolve a given image with an arbitrary image kernel using
9942
multiplication in the Fourier domain.
9945
This filter produces output equivalent to the output of the ConvolutionImageFilter . However, it takes advantage of the convolution theorem to
9946
accelerate the convolution computation when the kernel is large.
9950
This filter ignores the spacing, origin, and orientation of the kernel
9951
image and treats them as identical to those in the input image.
9952
This code was adapted from the Insight Journal contribution:
9954
\"FFT Based Convolution\" by Gaetan Lehmann https://hdl.handle.net/10380/3154
9958
ConvolutionImageFilter
9960
itk::simple::FFTConvolution for the procedural interface
9962
itk::FFTConvolutionImageFilter for the Doxygen on the original ITK class.
9965
C++ includes: sitkFFTConvolutionImageFilter.h
9968
%feature("docstring") itk::simple::FFTConvolutionImageFilter::Execute "
9970
Execute the filter on the input images
9974
%feature("docstring") itk::simple::FFTConvolutionImageFilter::Execute "
9976
Execute the filter on the input images with the given parameters
9980
%feature("docstring") itk::simple::FFTConvolutionImageFilter::FFTConvolutionImageFilter "
9982
Default Constructor that takes no arguments and initializes default
9987
%feature("docstring") itk::simple::FFTConvolutionImageFilter::GetBoundaryCondition "
9990
%feature("docstring") itk::simple::FFTConvolutionImageFilter::GetName "
9996
%feature("docstring") itk::simple::FFTConvolutionImageFilter::GetNormalize "
9999
%feature("docstring") itk::simple::FFTConvolutionImageFilter::GetOutputRegionMode "
10002
%feature("docstring") itk::simple::FFTConvolutionImageFilter::NormalizeOff "
10005
%feature("docstring") itk::simple::FFTConvolutionImageFilter::NormalizeOn "
10007
Set the value of Normalize to true or false respectfully.
10011
%feature("docstring") itk::simple::FFTConvolutionImageFilter::SetBoundaryCondition "
10014
%feature("docstring") itk::simple::FFTConvolutionImageFilter::SetNormalize "
10016
Normalize the output image by the sum of the kernel components
10020
%feature("docstring") itk::simple::FFTConvolutionImageFilter::SetOutputRegionMode "
10023
%feature("docstring") itk::simple::FFTConvolutionImageFilter::ToString "
10025
Print ourselves out
10029
%feature("docstring") itk::simple::FFTConvolutionImageFilter::~FFTConvolutionImageFilter "
10036
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter "
10038
Calculate normalized cross correlation using FFTs.
10041
This filter calculates the normalized cross correlation (NCC) of two
10042
images using FFTs instead of spatial correlation. It is much faster
10043
than spatial correlation for reasonably large structuring elements.
10044
This filter is a subclass of the more general MaskedFFTNormalizedCorrelationImageFilter and operates by essentially setting the masks in that algorithm to
10045
images of ones. As described in detail in the references below, there
10046
is no computational overhead to utilizing the more general masked
10047
algorithm because the FFTs of the images of ones are still necessary
10048
for the computations.
10050
Inputs: Two images are required as inputs, fixedImage and movingImage.
10051
In the context of correlation, inputs are often defined as: \"image\"
10052
and \"template\". In this filter, the fixedImage plays the role of the
10053
image, and the movingImage plays the role of the template. However,
10054
this filter is capable of correlating any two images and is not
10055
restricted to small movingImages (templates).
10057
Optional parameters: The RequiredNumberOfOverlappingPixels enables the
10058
user to specify how many voxels of the two images must overlap; any
10059
location in the correlation map that results from fewer than this
10060
number of voxels will be set to zero. Larger values zero-out pixels on
10061
a larger border around the correlation image. Thus, larger values
10062
remove less stable computations but also limit the capture range. If
10063
RequiredNumberOfOverlappingPixels is set to 0, the default, no zeroing
10066
Image size: fixedImage and movingImage need not be the same size.
10067
Furthermore, whereas some algorithms require that the \"template\" be
10068
smaller than the \"image\" because of errors in the regions where the
10069
two are not fully overlapping, this filter has no such restriction.
10071
Image spacing: Since the computations are done in the pixel domain, all
10072
input images must have the same spacing.
10074
Outputs; The output is an image of RealPixelType that is the NCC of
10075
the two images and its values range from -1.0 to 1.0. The size of this
10076
NCC image is, by definition, size(fixedImage) + size(movingImage) - 1.
10078
Example filter usage:
10082
The pixel type of the output image must be of real type (float or
10083
double). ConceptChecking is used to enforce the output pixel type. You
10084
will get a compilation error if the pixel type of the output image is
10085
not float or double.
10086
References: 1) D. Padfield. \"Masked object registration in the
10087
Fourier domain.\" Transactions on Image Processing. 2) D. Padfield. \"Masked FFT registration\". In Proc.
10088
Computer Vision and Pattern Recognition, 2010.
10091
: Dirk Padfield, GE Global Research, padfield@research.ge.com
10094
itk::simple::FFTNormalizedCorrelation for the procedural interface
10096
itk::FFTNormalizedCorrelationImageFilter for the Doxygen on the original ITK class.
10099
C++ includes: sitkFFTNormalizedCorrelationImageFilter.h
10102
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::Execute "
10104
Execute the filter on the input images
10108
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::Execute "
10110
Execute the filter on the input images with the given parameters
10114
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::FFTNormalizedCorrelationImageFilter "
10116
Default Constructor that takes no arguments and initializes default
10121
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::GetName "
10127
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::GetRequiredNumberOfOverlappingPixels "
10130
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::SetRequiredNumberOfOverlappingPixels "
10133
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::ToString "
10135
Print ourselves out
10139
%feature("docstring") itk::simple::FFTNormalizedCorrelationImageFilter::~FFTNormalizedCorrelationImageFilter "
10146
%feature("docstring") itk::simple::FFTPadImageFilter "
10148
Pad an image to make it suitable for an FFT transformation.
10151
FFT filters usually requires a specific image size. The size is
10152
decomposed in several prime factors, and the filter only supports
10153
prime factors up to a maximum value. This filter automatically finds
10154
the greatest prime factor required by the available implementation and
10155
pads the input appropriately.
10157
This code was adapted from the Insight Journal contribution:
10159
\"FFT Based Convolution\" by Gaetan Lehmann https://hdl.handle.net/10380/3154
10165
FFTShiftImageFilter
10167
itk::simple::FFTPad for the procedural interface
10169
itk::FFTPadImageFilter for the Doxygen on the original ITK class.
10172
C++ includes: sitkFFTPadImageFilter.h
10175
%feature("docstring") itk::simple::FFTPadImageFilter::Execute "
10177
Execute the filter on the input image
10181
%feature("docstring") itk::simple::FFTPadImageFilter::Execute "
10183
Execute the filter on the input image with the given parameters
10187
%feature("docstring") itk::simple::FFTPadImageFilter::FFTPadImageFilter "
10189
Default Constructor that takes no arguments and initializes default
10194
%feature("docstring") itk::simple::FFTPadImageFilter::GetBoundaryCondition "
10197
%feature("docstring") itk::simple::FFTPadImageFilter::GetName "
10203
%feature("docstring") itk::simple::FFTPadImageFilter::GetSizeGreatestPrimeFactor "
10205
Set/Get the greatest prime factor allowed on the size of the padded
10206
image. The filter increase the size of the image to reach a size with
10207
the greatest prime factor smaller or equal to the specified value. The
10208
default value is 13, which is the greatest prime number for which the
10209
FFT are precomputed in FFTW, and thus gives very good performance. A
10210
greatest prime factor of 2 produce a size which is a power of 2, and
10211
thus is suitable for vnl base fft filters. A greatest prime factor of
10212
1 or less - typically 0 - disable the extra padding.
10216
%feature("docstring") itk::simple::FFTPadImageFilter::SetBoundaryCondition "
10219
%feature("docstring") itk::simple::FFTPadImageFilter::SetSizeGreatestPrimeFactor "
10221
Set/Get the greatest prime factor allowed on the size of the padded
10222
image. The filter increase the size of the image to reach a size with
10223
the greatest prime factor smaller or equal to the specified value. The
10224
default value is 13, which is the greatest prime number for which the
10225
FFT are precomputed in FFTW, and thus gives very good performance. A
10226
greatest prime factor of 2 produce a size which is a power of 2, and
10227
thus is suitable for vnl base fft filters. A greatest prime factor of
10228
1 or less - typically 0 - disable the extra padding.
10232
%feature("docstring") itk::simple::FFTPadImageFilter::ToString "
10234
Print ourselves out
10238
%feature("docstring") itk::simple::FFTPadImageFilter::~FFTPadImageFilter "
10245
%feature("docstring") itk::simple::FFTShiftImageFilter "
10247
Shift the zero-frequency components of a Fourier transform to the
10248
center of the image.
10251
The Fourier transform produces an image where the zero frequency
10252
components are in the corner of the image, making it difficult to
10253
understand. This filter shifts the component to the center of the
10257
For images with an odd-sized dimension, applying this filter twice
10258
will not produce the same image as the original one without using
10259
SetInverse(true) on one (and only one) of the two filters.
10260
https://hdl.handle.net/1926/321
10263
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
10264
de Jouy-en-Josas, France.
10267
ForwardFFTImageFilter , InverseFFTImageFilter
10269
itk::simple::FFTShift for the procedural interface
10271
itk::FFTShiftImageFilter for the Doxygen on the original ITK class.
10274
C++ includes: sitkFFTShiftImageFilter.h
10277
%feature("docstring") itk::simple::FFTShiftImageFilter::Execute "
10279
Execute the filter on the input image
10283
%feature("docstring") itk::simple::FFTShiftImageFilter::Execute "
10285
Execute the filter on the input image with the given parameters
10289
%feature("docstring") itk::simple::FFTShiftImageFilter::FFTShiftImageFilter "
10291
Default Constructor that takes no arguments and initializes default
10296
%feature("docstring") itk::simple::FFTShiftImageFilter::GetInverse "
10298
Set/Get whether the filter must invert the transform or not. This
10299
option has no effect if none of the size of the input image is even,
10300
but is required to restore the original image if at least one of the
10301
dimensions has an odd size.
10305
%feature("docstring") itk::simple::FFTShiftImageFilter::GetName "
10311
%feature("docstring") itk::simple::FFTShiftImageFilter::InverseOff "
10314
%feature("docstring") itk::simple::FFTShiftImageFilter::InverseOn "
10316
Set the value of Inverse to true or false respectfully.
10320
%feature("docstring") itk::simple::FFTShiftImageFilter::SetInverse "
10322
Set/Get whether the filter must invert the transform or not. This
10323
option has no effect if none of the size of the input image is even,
10324
but is required to restore the original image if at least one of the
10325
dimensions has an odd size.
10329
%feature("docstring") itk::simple::FFTShiftImageFilter::ToString "
10331
Print ourselves out
10335
%feature("docstring") itk::simple::FFTShiftImageFilter::~FFTShiftImageFilter "
10342
%feature("docstring") itk::simple::FastApproximateRankImageFilter "
10344
A separable rank filter.
10347
Medians aren't separable, but if you want a large robust smoother to
10348
be relatively quick then it is worthwhile pretending that they are.
10350
This code was contributed in the Insight Journal paper: \"Efficient
10351
implementation of kernel filtering\" by Beare R., Lehmann G https://hdl.handle.net/1926/555 http://www.insight-journal.org/browse/publication/160
10357
itk::simple::FastApproximateRank for the procedural interface
10359
itk::FastApproximateRankImageFilter for the Doxygen on the original ITK class.
10362
C++ includes: sitkFastApproximateRankImageFilter.h
10365
%feature("docstring") itk::simple::FastApproximateRankImageFilter::Execute "
10367
Execute the filter on the input image
10371
%feature("docstring") itk::simple::FastApproximateRankImageFilter::Execute "
10373
Execute the filter on the input image with the given parameters
10377
%feature("docstring") itk::simple::FastApproximateRankImageFilter::FastApproximateRankImageFilter "
10379
Default Constructor that takes no arguments and initializes default
10384
%feature("docstring") itk::simple::FastApproximateRankImageFilter::GetName "
10390
%feature("docstring") itk::simple::FastApproximateRankImageFilter::GetRadius "
10393
%feature("docstring") itk::simple::FastApproximateRankImageFilter::GetRank "
10396
%feature("docstring") itk::simple::FastApproximateRankImageFilter::SetRadius "
10399
%feature("docstring") itk::simple::FastApproximateRankImageFilter::SetRadius "
10401
Set the values of the Radius vector all to value
10405
%feature("docstring") itk::simple::FastApproximateRankImageFilter::SetRank "
10408
%feature("docstring") itk::simple::FastApproximateRankImageFilter::ToString "
10410
Print ourselves out
10414
%feature("docstring") itk::simple::FastApproximateRankImageFilter::~FastApproximateRankImageFilter "
10421
%feature("docstring") itk::simple::FastMarchingBaseImageFilter "
10423
Fast Marching Method on Image .
10426
The speed function can be specified as a speed image or a speed
10427
constant. The speed image is set using the method SetInput(). If the
10428
speed image is ITK_NULLPTR, a constant speed function is used and is
10429
specified using method the SetSpeedConstant() .
10431
If the speed function is constant and of value one, fast marching
10432
results is an approximate distance function from the initial alive
10435
There are two ways to specify the output image information (
10436
LargestPossibleRegion, Spacing, Origin):
10439
it is copied directly from the input speed image
10441
it is specified by the user. Default values are used if the user does
10442
not specify all the information.
10443
The output information is computed as follows.
10445
If the speed image is ITK_NULLPTR or if the OverrideOutputInformation
10446
is set to true, the output information is set from user specified
10447
parameters. These parameters can be specified using methods
10450
FastMarchingImageFilterBase::SetOutputRegion() ,
10452
FastMarchingImageFilterBase::SetOutputSpacing() ,
10454
FastMarchingImageFilterBase::SetOutputDirection() ,
10456
FastMarchingImageFilterBase::SetOutputOrigin() .
10457
Else the output information is copied from the input speed image.
10459
Implementation of this class is based on Chapter 8 of \"Level Set
10460
Methods and Fast Marching Methods\", J.A. Sethian, Cambridge Press,
10461
Second edition, 1999.
10463
For an alternative implementation, see itk::FastMarchingImageFilter .
10471
FastMarchingImageFilter
10473
ImageFastMarchingTraits
10475
ImageFastMarchingTraits2
10477
itk::simple::FastMarchingBase for the procedural interface
10479
itk::FastMarchingImageFilterBase for the Doxygen on the original ITK class.
10482
C++ includes: sitkFastMarchingBaseImageFilter.h
10485
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::AddTrialPoint "
10491
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::ClearTrialPoints "
10497
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::Execute "
10499
Execute the filter on the input image
10503
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::Execute "
10505
Execute the filter on the input image with the given parameters
10509
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::FastMarchingBaseImageFilter "
10511
Default Constructor that takes no arguments and initializes default
10516
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::GetName "
10522
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::GetNormalizationFactor "
10524
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10525
pixel types to represent the speed.
10529
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::GetStoppingValue "
10531
Get the Fast Marching algorithm Stopping Value.
10535
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::GetTopologyCheck "
10538
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::GetTrialPoints "
10544
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::SetNormalizationFactor "
10546
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10547
pixel types to represent the speed.
10551
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::SetStoppingValue "
10553
Set the Fast Marching algorithm Stopping Value. The Fast Marching
10554
algorithm is terminated when the value of the smallest trial point is
10555
greater than the stopping value.
10559
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::SetTopologyCheck "
10562
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::SetTrialPoints "
10564
Set trial points. The default trial value (i.e. 0.0) is used for each
10569
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::ToString "
10571
Print ourselves out
10575
%feature("docstring") itk::simple::FastMarchingBaseImageFilter::~FastMarchingBaseImageFilter "
10582
%feature("docstring") itk::simple::FastMarchingImageFilter "
10584
Solve an Eikonal equation using Fast Marching.
10587
Fast marching solves an Eikonal equation where the speed is always
10588
non-negative and depends on the position only. Starting from an
10589
initial position on the front, fast marching systematically moves the
10590
front forward one grid point at a time.
10592
Updates are preformed using an entropy satisfy scheme where only
10593
\"upwind\" neighborhoods are used. This implementation of Fast
10594
Marching uses a std::priority_queue to locate the next proper grid
10595
position to update.
10597
Fast Marching sweeps through N grid points in (N log N) steps to
10598
obtain the arrival time value as the front propagates through the
10601
Implementation of this class is based on Chapter 8 of \"Level Set
10602
Methods and Fast Marching Methods\", J.A. Sethian, Cambridge Press,
10603
Second edition, 1999.
10605
This class is templated over the level set image type and the speed
10606
image type. The initial front is specified by two containers: one
10607
containing the known points and one containing the trial points. Alive
10608
points are those that are already part of the object, and trial points
10609
are considered for inclusion. In order for the filter to evolve, at
10610
least some trial points must be specified. These can for instance be
10611
specified as the layer of pixels around the alive points.
10613
The speed function can be specified as a speed image or a speed
10614
constant. The speed image is set using the method SetInput() . If the
10615
speed image is ITK_NULLPTR, a constant speed function is used and is
10616
specified using method the SetSpeedConstant() .
10618
If the speed function is constant and of value one, fast marching
10619
results in an approximate distance function from the initial alive
10620
points. FastMarchingImageFilter is used in the ReinitializeLevelSetImageFilter object to create a signed distance function from the zero level set.
10622
The algorithm can be terminated early by setting an appropriate
10623
stopping value. The algorithm terminates when the current arrival time
10624
being processed is greater than the stopping value.
10626
There are two ways to specify the output image information (
10627
LargestPossibleRegion, Spacing, Origin): (a) it is copied directly
10628
from the input speed image or (b) it is specified by the user. Default
10629
values are used if the user does not specify all the information.
10631
The output information is computed as follows. If the speed image is
10632
ITK_NULLPTR or if the OverrideOutputInformation is set to true, the
10633
output information is set from user specified parameters. These
10634
parameters can be specified using methods SetOutputRegion() ,
10635
SetOutputSpacing() , SetOutputDirection() , and SetOutputOrigin() .
10636
Else if the speed image is not ITK_NULLPTR, the output information is
10637
copied from the input speed image.
10639
For an alternative implementation, see itk::FastMarchingImageFilter .
10641
Possible Improvements: In the current implementation,
10642
std::priority_queue only allows taking nodes out from the front and
10643
putting nodes in from the back. To update a value already on the heap,
10644
a new node is added to the heap. The defunct old node is left on the
10645
heap. When it is removed from the top, it will be recognized as
10646
invalid and not used. Future implementations can implement the heap in
10647
a different way allowing the values to be updated. This will generally
10648
require some sift-up and sift-down functions and an image of back-
10649
pointers going from the image to heap in order to locate the node
10650
which is to be updated.
10654
FastMarchingImageFilterBase
10656
LevelSetTypeDefault
10658
itk::simple::FastMarching for the procedural interface
10660
itk::FastMarchingImageFilter for the Doxygen on the original ITK class.
10663
C++ includes: sitkFastMarchingImageFilter.h
10666
%feature("docstring") itk::simple::FastMarchingImageFilter::AddTrialPoint "
10668
Add TrialPoints point.
10672
%feature("docstring") itk::simple::FastMarchingImageFilter::ClearTrialPoints "
10674
Remove all TrialPoints points.
10678
%feature("docstring") itk::simple::FastMarchingImageFilter::Execute "
10680
Execute the filter on the input image
10684
%feature("docstring") itk::simple::FastMarchingImageFilter::Execute "
10686
Execute the filter on the input image with the given parameters
10690
%feature("docstring") itk::simple::FastMarchingImageFilter::FastMarchingImageFilter "
10692
Default Constructor that takes no arguments and initializes default
10697
%feature("docstring") itk::simple::FastMarchingImageFilter::GetName "
10703
%feature("docstring") itk::simple::FastMarchingImageFilter::GetNormalizationFactor "
10705
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10706
pixel types to represent the speed.
10710
%feature("docstring") itk::simple::FastMarchingImageFilter::GetStoppingValue "
10712
Get the Fast Marching algorithm Stopping Value.
10716
%feature("docstring") itk::simple::FastMarchingImageFilter::GetTrialPoints "
10718
Get the container of Trial Points representing the initial front.
10722
%feature("docstring") itk::simple::FastMarchingImageFilter::SetNormalizationFactor "
10724
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10725
pixel types to represent the speed.
10729
%feature("docstring") itk::simple::FastMarchingImageFilter::SetStoppingValue "
10731
Set the Fast Marching algorithm Stopping Value. The Fast Marching
10732
algorithm is terminated when the value of the smallest trial point is
10733
greater than the stopping value.
10737
%feature("docstring") itk::simple::FastMarchingImageFilter::SetTrialPoints "
10739
Set the container of Trial Points representing the initial front.
10740
Trial points are represented as a VectorContainer of LevelSetNodes.
10744
%feature("docstring") itk::simple::FastMarchingImageFilter::ToString "
10746
Print ourselves out
10750
%feature("docstring") itk::simple::FastMarchingImageFilter::~FastMarchingImageFilter "
10757
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter "
10759
Generates the upwind gradient field of fast marching arrival times.
10762
This filter adds some extra functionality to its base class. While the
10763
solution T(x) of the Eikonal equation is being generated by the base
10764
class with the fast marching method, the filter generates the upwind
10765
gradient vectors of T(x), storing them in an image.
10767
Since the Eikonal equation generates the arrival times of a wave
10768
travelling at a given speed, the generated gradient vectors can be
10769
interpreted as the slowness (1/velocity) vectors of the front (the
10770
quantity inside the modulus operator in the Eikonal equation).
10772
Gradient vectors are computed using upwind finite differences, that
10773
is, information only propagates from points where the wavefront has
10774
already passed. This is consistent with how the fast marching method
10777
One more extra feature is the possibility to define a set of Target
10778
points where the propagation stops. This can be used to avoid
10779
computing the Eikonal solution for the whole domain. The front can be
10780
stopped either when one Target point is reached or all Target points
10781
are reached. The propagation can stop after a time TargetOffset has
10782
passed since the stop condition is met. This way the solution is
10783
computed a bit downstream the Target points, so that the level sets of
10784
T(x) corresponding to the Target are smooth.
10786
For an alternative implementation, see itk::FastMarchingUpwindGradientImageFilterBase .
10789
Luca Antiga Ph.D. Biomedical Technologies Laboratory, Bioengineering
10790
Department, Mario Negri Institute, Italy.
10793
itk::simple::FastMarchingUpwindGradient for the procedural interface
10795
itk::FastMarchingUpwindGradientImageFilter for the Doxygen on the original ITK class.
10798
C++ includes: sitkFastMarchingUpwindGradientImageFilter.h
10801
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::AddTargetPoint "
10803
Add TargetPoints point.
10807
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::AddTrialPoint "
10809
Add TrialPoints point.
10813
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::ClearTargetPoints "
10815
Remove all TargetPoints points.
10819
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::ClearTrialPoints "
10821
Remove all TrialPoints points.
10825
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::Execute "
10827
Execute the filter on the input image
10831
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::Execute "
10833
Execute the filter on the input image with the given parameters
10837
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::FastMarchingUpwindGradientImageFilter "
10839
Default Constructor that takes no arguments and initializes default
10844
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetGradientImage "
10846
Get the gradient image.
10848
This is a measurement. Its value is updated in the Execute methods, so
10849
the value will only be valid after an execution.
10853
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetName "
10859
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetNormalizationFactor "
10861
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10862
pixel types to represent the speed.
10866
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetNumberOfTargets "
10868
Get the number of targets.
10872
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetTargetOffset "
10874
Get the TargetOffset ivar.
10878
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetTargetPoints "
10880
Get the container of Target Points.
10884
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetTargetValue "
10886
Get the arrival time corresponding to the last reached target. If
10887
TargetReachedMode is set to NoTargets, TargetValue contains the last
10888
(aka largest) Eikonal solution value generated.
10890
This is a measurement. Its value is updated in the Execute methods, so
10891
the value will only be valid after an execution.
10895
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::GetTrialPoints "
10898
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::SetNormalizationFactor "
10900
Set/Get the Normalization Factor for the Speed Image . The values in the Speed Image is divided by this factor. This allows the use of images with integer
10901
pixel types to represent the speed.
10905
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::SetNumberOfTargets "
10908
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::SetTargetOffset "
10910
Set how long (in terms of arrival times) after targets are reached the
10911
front must stop. This is useful to ensure that the level set of target
10912
arrival time is smooth.
10916
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::SetTargetPoints "
10918
Set the container of Target Points. If a target point is reached, the
10919
propagation stops. Trial points are represented as a VectorContainer of LevelSetNodes.
10923
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::SetTrialPoints "
10926
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::ToString "
10928
Print ourselves out
10932
%feature("docstring") itk::simple::FastMarchingUpwindGradientImageFilter::~FastMarchingUpwindGradientImageFilter "
10939
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter "
10941
Deformably register two images using a symmetric forces demons
10945
This class was contributed by Tom Vercauteren, INRIA & Mauna Kea
10946
Technologies based on a variation of the DemonsRegistrationFilter .
10948
FastSymmetricForcesDemonsRegistrationFilter implements the demons deformable algorithm that register two images
10949
by computing the deformation field which will map a moving image onto
10952
A deformation field is represented as a image whose pixel type is some
10953
vector type with at least N elements, where N is the dimension of the
10954
fixed image. The vector type must support element access via operator
10955
[]. It is assumed that the vector elements behave like floating point
10958
This class is templated over the fixed image type, moving image type
10959
and the deformation field type.
10961
The input fixed and moving images are set via methods SetFixedImage
10962
and SetMovingImage respectively. An initial deformation field maybe
10963
set via SetInitialDisplacementField or SetInput. If no initial field
10964
is set, a zero field is used as the initial condition.
10966
The output deformation field can be obtained via methods GetOutput or
10967
GetDisplacementField.
10969
This class make use of the finite difference solver hierarchy. Update
10970
for each iteration is computed in DemonsRegistrationFunction .
10973
Tom Vercauteren, INRIA & Mauna Kea Technologies
10974
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/510
10978
This filter assumes that the fixed image type, moving image type and
10979
deformation field type all have the same number of dimensions.
10982
DemonsRegistrationFilter
10984
DemonsRegistrationFunction
10986
itk::FastSymmetricForcesDemonsRegistrationFilter for the Doxygen on the original ITK class.
10989
C++ includes: sitkFastSymmetricForcesDemonsRegistrationFilter.h
10992
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::Execute "
10994
Execute the filter on the input image
10998
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::Execute "
11001
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::Execute "
11003
Execute the filter on the input image with the given parameters
11007
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::Execute "
11010
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::FastSymmetricForcesDemonsRegistrationFilter "
11012
Default Constructor that takes no arguments and initializes default
11017
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetElapsedIterations "
11019
Number of iterations run.
11022
This is an active measurement. It may be accessed while the filter is
11023
being executing in command call-backs and can be accessed after
11028
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetIntensityDifferenceThreshold "
11031
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetMaximumError "
11033
Set/Get the desired maximum error of the Guassian kernel approximate.
11037
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetMaximumKernelWidth "
11039
Set/Get the desired limits of the Gaussian kernel width.
11043
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetMaximumRMSError "
11046
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetMaximumUpdateStepLength "
11049
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetMetric "
11051
Get the metric value. The metric value is the mean square difference
11052
in intensity between the fixed image and transforming moving image
11053
computed over the the overlapping region between the two images. This
11054
value is calculated for the current iteration
11056
This is an active measurement. It may be accessed while the filter is
11057
being executing in command call-backs and can be accessed after
11062
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetName "
11068
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetNumberOfIterations "
11071
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetRMSChange "
11073
Set/Get the root mean squared change of the previous iteration. May
11074
not be used by all solvers.
11076
This is a measurement. Its value is updated in the Execute methods, so
11077
the value will only be valid after an execution.
11081
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetSmoothDisplacementField "
11083
Set/Get whether the displacement field is smoothed (regularized).
11084
Smoothing the displacement yields a solution elastic in nature. If
11085
SmoothDisplacementField is on, then the displacement field is smoothed
11086
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
11090
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetSmoothUpdateField "
11092
Set/Get whether the update field is smoothed (regularized). Smoothing
11093
the update field yields a solution viscous in nature. If
11094
SmoothUpdateField is on, then the update field is smoothed with a
11095
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
11099
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetStandardDeviations "
11101
Set/Get the Gaussian smoothing standard deviations for the
11102
displacement field. The values are set with respect to pixel
11107
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetUpdateFieldStandardDeviations "
11109
Set the Gaussian smoothing standard deviations for the update field.
11110
The values are set with respect to pixel coordinates.
11114
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetUseGradientType "
11117
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::GetUseImageSpacing "
11120
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetIntensityDifferenceThreshold "
11122
Set/Get the threshold below which the absolute difference of intensity
11123
yields a match. When the intensities match between a moving and fixed
11124
image pixel, the update vector (for that iteration) will be the zero
11125
vector. Default is 0.001.
11129
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetMaximumError "
11131
Set/Get the desired maximum error of the Guassian kernel approximate.
11135
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetMaximumKernelWidth "
11137
Set/Get the desired limits of the Gaussian kernel width.
11141
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetMaximumRMSError "
11144
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetMaximumUpdateStepLength "
11147
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetNumberOfIterations "
11150
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetSmoothDisplacementField "
11152
Set/Get whether the displacement field is smoothed (regularized).
11153
Smoothing the displacement yields a solution elastic in nature. If
11154
SmoothDisplacementField is on, then the displacement field is smoothed
11155
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
11159
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetSmoothUpdateField "
11161
Set/Get whether the update field is smoothed (regularized). Smoothing
11162
the update field yields a solution viscous in nature. If
11163
SmoothUpdateField is on, then the update field is smoothed with a
11164
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
11168
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetStandardDeviations "
11170
Set/Get the Gaussian smoothing standard deviations for the
11171
displacement field. The values are set with respect to pixel
11176
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetStandardDeviations "
11178
Set the values of the StandardDeviations vector all to value
11182
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
11184
Set the Gaussian smoothing standard deviations for the update field.
11185
The values are set with respect to pixel coordinates.
11189
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
11191
Set the values of the UpdateFieldStandardDeviations vector all to
11196
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetUseGradientType "
11199
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SetUseImageSpacing "
11202
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SmoothDisplacementFieldOff "
11205
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SmoothDisplacementFieldOn "
11207
Set the value of SmoothDisplacementField to true or false
11212
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SmoothUpdateFieldOff "
11215
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::SmoothUpdateFieldOn "
11217
Set the value of SmoothUpdateField to true or false respectfully.
11221
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::ToString "
11223
Print ourselves out
11227
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::UseImageSpacingOff "
11230
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::UseImageSpacingOn "
11232
Set the value of UseImageSpacing to true or false respectfully.
11236
%feature("docstring") itk::simple::FastSymmetricForcesDemonsRegistrationFilter::~FastSymmetricForcesDemonsRegistrationFilter "
11243
%feature("docstring") itk::simple::FlipImageFilter "
11245
Flips an image across user specified axes.
11248
FlipImageFilter flips an image across user specified axes. The flip axes are set via
11249
method SetFlipAxes( array ) where the input is a
11250
FixedArray<bool,ImageDimension>. The image is flipped across axes for
11251
which array[i] is true.
11253
In terms of grid coordinates the image is flipped within the
11254
LargestPossibleRegion of the input image. As such, the
11255
LargestPossibleRegion of the output image is the same as the input.
11257
In terms of geometric coordinates, the output origin is such that the
11258
image is flipped with respect to the coordinate axes.
11264
Flip an image over specified axes
11266
itk::simple::Flip for the procedural interface
11268
itk::FlipImageFilter for the Doxygen on the original ITK class.
11272
C++ includes: sitkFlipImageFilter.h
11275
%feature("docstring") itk::simple::FlipImageFilter::Execute "
11277
Execute the filter on the input image
11281
%feature("docstring") itk::simple::FlipImageFilter::Execute "
11283
Execute the filter on the input image with the given parameters
11287
%feature("docstring") itk::simple::FlipImageFilter::FlipAboutOriginOff "
11290
%feature("docstring") itk::simple::FlipImageFilter::FlipAboutOriginOn "
11292
Set the value of FlipAboutOrigin to true or false respectfully.
11296
%feature("docstring") itk::simple::FlipImageFilter::FlipImageFilter "
11298
Default Constructor that takes no arguments and initializes default
11303
%feature("docstring") itk::simple::FlipImageFilter::GetFlipAboutOrigin "
11305
Controls how the output origin is computed. If FlipAboutOrigin is
11306
\"On\", the flip will occur about the origin of the axis, otherwise,
11307
the flip will occur about the center of the axis. Default is \"On\".
11311
%feature("docstring") itk::simple::FlipImageFilter::GetFlipAxes "
11313
Set/Get the axis to be flipped. The image is flipped along axes for
11314
which array[i] is true. Default is false.
11318
%feature("docstring") itk::simple::FlipImageFilter::GetName "
11324
%feature("docstring") itk::simple::FlipImageFilter::SetFlipAboutOrigin "
11326
Controls how the output origin is computed. If FlipAboutOrigin is
11327
\"On\", the flip will occur about the origin of the axis, otherwise,
11328
the flip will occur about the center of the axis. Default is \"On\".
11332
%feature("docstring") itk::simple::FlipImageFilter::SetFlipAxes "
11334
Set/Get the axis to be flipped. The image is flipped along axes for
11335
which array[i] is true. Default is false.
11339
%feature("docstring") itk::simple::FlipImageFilter::ToString "
11341
Print ourselves out
11345
%feature("docstring") itk::simple::FlipImageFilter::~FlipImageFilter "
11352
%feature("docstring") itk::simple::ForwardFFTImageFilter "
11354
Base class for forward Fast Fourier Transform .
11357
This is a base class for the \"forward\" or \"direct\" discrete
11358
Fourier Transform . This is an abstract base class: the actual implementation is
11359
provided by the best child class available on the system when the
11360
object is created via the object factory system.
11362
This class transforms a real input image into its full complex Fourier
11363
transform. The Fourier transform of a real input image has Hermitian
11364
symmetry: $ f(\\\\mathbf{x}) = f^*(-\\\\mathbf{x}) $ . That is, when the result of the transform is split in half along
11365
the x-dimension, the values in the second half of the transform are
11366
the complex conjugates of values in the first half reflected about the
11367
center of the image in each dimension.
11369
This filter works only for real single-component input image types.
11373
InverseFFTImageFilter , FFTComplexToComplexImageFilter
11375
itk::simple::ForwardFFT for the procedural interface
11377
itk::ForwardFFTImageFilter for the Doxygen on the original ITK class.
11380
C++ includes: sitkForwardFFTImageFilter.h
11383
%feature("docstring") itk::simple::ForwardFFTImageFilter::Execute "
11385
Execute the filter on the input image
11389
%feature("docstring") itk::simple::ForwardFFTImageFilter::ForwardFFTImageFilter "
11391
Default Constructor that takes no arguments and initializes default
11396
%feature("docstring") itk::simple::ForwardFFTImageFilter::GetName "
11402
%feature("docstring") itk::simple::ForwardFFTImageFilter::ToString "
11404
Print ourselves out
11408
%feature("docstring") itk::simple::ForwardFFTImageFilter::~ForwardFFTImageFilter "
11415
%feature("docstring") itk::simple::FunctionCommand "
11417
A Command class which allows setting an external function, or member function.
11419
C++ includes: sitkFunctionCommand.h
11422
%feature("docstring") itk::simple::FunctionCommand::Execute "
11424
The method that defines action to be taken by the command
11428
%feature("docstring") itk::simple::FunctionCommand::FunctionCommand "
11431
%feature("docstring") itk::simple::FunctionCommand::SetCallbackFunction "
11433
Generic method to set a class's member function to be called in the
11438
%feature("docstring") itk::simple::FunctionCommand::SetCallbackFunction "
11440
Set a C-Style function to be called in the Execute method
11444
%feature("docstring") itk::simple::FunctionCommand::SetCallbackFunction "
11446
Set a C-Style function with a void* clientData as an argument. The
11447
caller is responsible for managing the life of the clientData and that
11448
it's valid when Execute is called with the clientData.
11453
%feature("docstring") itk::simple::GaborImageSource "
11455
Generate an n-dimensional image of a Gabor filter.
11458
GaborImageSource generates an image of either the real (i.e. symmetric) or complex
11459
(i.e. antisymmetric) part of the Gabor filter with the orientation
11460
directed along the x-axis. The GaborKernelFunction is used to evaluate the contribution along the x-axis whereas a non-
11461
normalized 1-D Gaussian envelope provides the contribution in each of
11462
the remaining N dimensions. Orientation can be manipulated via the Transform classes of the toolkit.
11464
The output image may be of any dimension.
11466
This implementation was contributed as a paper to the Insight Journal https://hdl.handle.net/1926/500
11468
itk::simple::GaborImageSource for the procedural interface
11470
itk::GaborImageSource for the Doxygen on the original ITK class.
11473
C++ includes: sitkGaborImageSource.h
11476
%feature("docstring") itk::simple::GaborImageSource::Execute "
11478
Execute the filter on the input image
11482
%feature("docstring") itk::simple::GaborImageSource::Execute "
11484
Execute the filter on the input image with the given parameters
11488
%feature("docstring") itk::simple::GaborImageSource::GaborImageSource "
11490
Default Constructor that takes no arguments and initializes default
11495
%feature("docstring") itk::simple::GaborImageSource::GetDirection "
11498
%feature("docstring") itk::simple::GaborImageSource::GetFrequency "
11500
Set/Get the modulation frequency of the sine or cosine component.
11504
%feature("docstring") itk::simple::GaborImageSource::GetMean "
11506
Set/Get the mean in each direction.
11510
%feature("docstring") itk::simple::GaborImageSource::GetName "
11516
%feature("docstring") itk::simple::GaborImageSource::GetOrigin "
11519
%feature("docstring") itk::simple::GaborImageSource::GetOutputPixelType "
11522
%feature("docstring") itk::simple::GaborImageSource::GetSigma "
11524
Set/Get the the standard deviation in each direction.
11528
%feature("docstring") itk::simple::GaborImageSource::GetSize "
11531
%feature("docstring") itk::simple::GaborImageSource::GetSpacing "
11534
%feature("docstring") itk::simple::GaborImageSource::SetDirection "
11537
%feature("docstring") itk::simple::GaborImageSource::SetFrequency "
11539
Set/Get the modulation frequency of the sine or cosine component.
11543
%feature("docstring") itk::simple::GaborImageSource::SetMean "
11545
Set/Get the mean in each direction.
11549
%feature("docstring") itk::simple::GaborImageSource::SetMean "
11551
Set the values of the Mean vector all to value
11555
%feature("docstring") itk::simple::GaborImageSource::SetOrigin "
11558
%feature("docstring") itk::simple::GaborImageSource::SetOutputPixelType "
11561
%feature("docstring") itk::simple::GaborImageSource::SetSigma "
11563
Set/Get the the standard deviation in each direction.
11567
%feature("docstring") itk::simple::GaborImageSource::SetSigma "
11569
Set the values of the Sigma vector all to value
11573
%feature("docstring") itk::simple::GaborImageSource::SetSize "
11576
%feature("docstring") itk::simple::GaborImageSource::SetSpacing "
11579
%feature("docstring") itk::simple::GaborImageSource::ToString "
11581
Print ourselves out
11585
%feature("docstring") itk::simple::GaborImageSource::~GaborImageSource "
11592
%feature("docstring") itk::simple::GaussianImageSource "
11594
Generate an n-dimensional image of a Gaussian.
11597
GaussianImageSource generates an image of a Gaussian. m_Normalized determines whether or
11598
not the Gaussian is normalized (whether or not the sum over infinite
11599
space is 1.0) When creating an image, it is preferable to not
11600
normalize the Gaussian m_Scale scales the output of the Gaussian to
11601
span a range larger than 0->1, and is typically set to the maximum
11602
value of the output data type (for instance, 255 for uchars)
11604
The output image may be of any dimension.
11606
itk::simple::GaussianImageSource for the procedural interface
11608
itk::GaussianImageSource for the Doxygen on the original ITK class.
11611
C++ includes: sitkGaussianImageSource.h
11614
%feature("docstring") itk::simple::GaussianImageSource::Execute "
11616
Execute the filter on the input image
11620
%feature("docstring") itk::simple::GaussianImageSource::Execute "
11622
Execute the filter on the input image with the given parameters
11626
%feature("docstring") itk::simple::GaussianImageSource::GaussianImageSource "
11628
Default Constructor that takes no arguments and initializes default
11633
%feature("docstring") itk::simple::GaussianImageSource::GetDirection "
11636
%feature("docstring") itk::simple::GaussianImageSource::GetMean "
11638
Set/Get the mean in each direction.
11642
%feature("docstring") itk::simple::GaussianImageSource::GetName "
11648
%feature("docstring") itk::simple::GaussianImageSource::GetOrigin "
11651
%feature("docstring") itk::simple::GaussianImageSource::GetOutputPixelType "
11654
%feature("docstring") itk::simple::GaussianImageSource::GetScale "
11656
Gets and sets for Gaussian parameters Set/Get the scale factor to
11657
multiply the true value of the Gaussian.
11661
%feature("docstring") itk::simple::GaussianImageSource::GetSigma "
11663
Set/Get the standard deviation in each direction.
11667
%feature("docstring") itk::simple::GaussianImageSource::GetSize "
11670
%feature("docstring") itk::simple::GaussianImageSource::GetSpacing "
11673
%feature("docstring") itk::simple::GaussianImageSource::SetDirection "
11676
%feature("docstring") itk::simple::GaussianImageSource::SetMean "
11678
Set/Get the mean in each direction.
11682
%feature("docstring") itk::simple::GaussianImageSource::SetMean "
11684
Set the values of the Mean vector all to value
11688
%feature("docstring") itk::simple::GaussianImageSource::SetOrigin "
11691
%feature("docstring") itk::simple::GaussianImageSource::SetOutputPixelType "
11694
%feature("docstring") itk::simple::GaussianImageSource::SetScale "
11696
Gets and sets for Gaussian parameters Set/Get the scale factor to
11697
multiply the true value of the Gaussian.
11701
%feature("docstring") itk::simple::GaussianImageSource::SetSigma "
11703
Set/Get the standard deviation in each direction.
11707
%feature("docstring") itk::simple::GaussianImageSource::SetSigma "
11709
Set the values of the Sigma vector all to value
11713
%feature("docstring") itk::simple::GaussianImageSource::SetSize "
11716
%feature("docstring") itk::simple::GaussianImageSource::SetSpacing "
11719
%feature("docstring") itk::simple::GaussianImageSource::ToString "
11721
Print ourselves out
11725
%feature("docstring") itk::simple::GaussianImageSource::~GaussianImageSource "
11732
%feature("docstring") itk::simple::GenericException "
11734
The base SimpleITK exception class.
11736
C++ includes: sitkExceptionObject.h
11739
%feature("docstring") itk::simple::GenericException::GenericException "
11741
Default constructor. Needed to ensure the exception object can be
11746
%feature("docstring") itk::simple::GenericException::GenericException "
11749
%feature("docstring") itk::simple::GenericException::GenericException "
11751
Constructor. Needed to ensure the exception object can be copied.
11755
%feature("docstring") itk::simple::GenericException::GenericException "
11757
Constructor. Needed to ensure the exception object can be copied.
11761
%feature("docstring") itk::simple::GenericException::GenericException "
11763
Constructor. Needed to ensure the exception object can be copied.
11767
%feature("docstring") itk::simple::GenericException::GetDescription "
11770
%feature("docstring") itk::simple::GenericException::GetFile "
11772
What file did the exception occur in?
11776
%feature("docstring") itk::simple::GenericException::GetLine "
11778
What line did the exception occur in?
11782
%feature("docstring") itk::simple::GenericException::GetLocation "
11785
%feature("docstring") itk::simple::GenericException::GetNameOfClass "
11788
%feature("docstring") itk::simple::GenericException::ToString "
11790
Return a description of the error
11794
%feature("docstring") itk::simple::GenericException::what "
11797
%feature("docstring") itk::simple::GenericException::~GenericException "
11799
Virtual destructor needed for subclasses. Has to have empty throw().
11804
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter "
11806
Segments structures in images based on a user supplied edge potential
11811
The SegmentationLevelSetImageFilter class and the GeodesicActiveContourLevelSetFunction class contain additional information necessary to gain full
11812
understanding of how to use this filter.
11814
This class is a level set method segmentation filter. An initial
11815
contour is propagated outwards (or inwards) until it ''sticks'' to the
11816
shape boundaries. This is done by using a level set speed function
11817
based on a user supplied edge potential map.
11819
This filter requires two inputs. The first input is a initial level
11820
set. The initial level set is a real image which contains the initial
11821
contour/surface as the zero level set. For example, a signed distance
11822
function from the initial contour/surface is typically used. Unlike
11823
the simpler ShapeDetectionLevelSetImageFilter the initial contour does not have to lie wholly within the shape to
11824
be segmented. The initial contour is allow to overlap the shape
11825
boundary. The extra advection term in the update equation behaves like
11826
a doublet and attracts the contour to the boundary. This approach for
11827
segmentation follows that of Caselles et al (1997).
11829
The second input is the feature image. For this filter, this is the
11830
edge potential map. General characteristics of an edge potential map
11831
is that it has values close to zero in regions near the edges and
11832
values close to one inside the shape itself. Typically, the edge
11833
potential map is compute from the image gradient, for example:
11834
\\\\[ g(I) = 1 / ( 1 + | (\\\\nabla * G)(I)| ) \\\\] \\\\[ g(I) = \\\\exp^{-|(\\\\nabla * G)(I)|} \\\\]
11836
where $ I $ is image intensity and $ (\\\\nabla * G) $ is the derivative of Gaussian operator.
11839
See SegmentationLevelSetImageFilter and SparseFieldLevelSetImageFilter for more information on Inputs.
11841
The PropagationScaling parameter can be used to switch from
11842
propagation outwards (POSITIVE scaling parameter) versus propagating
11843
inwards (NEGATIVE scaling parameter).
11844
This implementation allows the user to set the weights between the
11845
propagation, advection and curvature term using methods SetPropagationScaling() , SetAdvectionScaling() , SetCurvatureScaling() . In general, the larger the CurvatureScaling, the smoother the
11846
resulting contour. To follow the implementation in Caselles et al
11847
paper, set the PropagationScaling to $ c $ (the inflation or ballon force) and AdvectionScaling and
11848
CurvatureScaling both to 1.0.
11851
The filter outputs a single, scalar, real-valued image. Negative
11852
values in the output image represent the inside of the segmented
11853
region and positive values in the image represent the outside of the
11854
segmented region. The zero crossings of the image correspond to the
11855
position of the propagating front.
11857
See SparseFieldLevelSetImageFilter and SegmentationLevelSetImageFilter for more information.
11860
\"Geodesic Active Contours\", V. Caselles, R. Kimmel and G. Sapiro.
11861
International Journal on Computer Vision, Vol 22, No. 1, pp 61-97,
11865
SegmentationLevelSetImageFilter
11867
GeodesicActiveContourLevelSetFunction
11869
SparseFieldLevelSetImageFilter
11871
itk::simple::GeodesicActiveContourLevelSet for the procedural interface
11873
itk::GeodesicActiveContourLevelSetImageFilter for the Doxygen on the original ITK class.
11876
C++ includes: sitkGeodesicActiveContourLevelSetImageFilter.h
11879
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::Execute "
11881
Execute the filter on the input images
11885
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::Execute "
11887
Execute the filter on the input images with the given parameters
11891
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GeodesicActiveContourLevelSetImageFilter "
11893
Default Constructor that takes no arguments and initializes default
11898
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetAdvectionScaling "
11901
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetCurvatureScaling "
11904
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetElapsedIterations "
11906
Number of iterations run.
11909
This is a measurement. Its value is updated in the Execute methods, so
11910
the value will only be valid after an execution.
11914
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetMaximumRMSError "
11917
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetName "
11923
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetNumberOfIterations "
11926
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetPropagationScaling "
11929
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetReverseExpansionDirection "
11932
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::GetRMSChange "
11934
The Root Mean Square of the levelset upon termination.
11937
This is a measurement. Its value is updated in the Execute methods, so
11938
the value will only be valid after an execution.
11942
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::ReverseExpansionDirectionOff "
11945
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::ReverseExpansionDirectionOn "
11947
Set the value of ReverseExpansionDirection to true or false
11952
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetAdvectionScaling "
11955
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetCurvatureScaling "
11958
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetMaximumRMSError "
11961
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetNumberOfIterations "
11964
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetPropagationScaling "
11967
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::SetReverseExpansionDirection "
11970
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::ToString "
11972
Print ourselves out
11976
%feature("docstring") itk::simple::GeodesicActiveContourLevelSetImageFilter::~GeodesicActiveContourLevelSetImageFilter "
11983
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter "
11985
This filter performs anisotropic diffusion on a scalar itk::Image using the classic Perona-Malik, gradient magnitude based equation
11986
implemented in itkGradientNDAnisotropicDiffusionFunction. For detailed
11987
information on anisotropic diffusion, see
11988
itkAnisotropicDiffusionFunction and
11989
itkGradientNDAnisotropicDiffusionFunction.
11992
The input to this filter should be a scalar itk::Image of any dimensionality. The output image will be a diffused copy of
11995
Please see the description of parameters given in
11996
itkAnisotropicDiffusionImageFilter.
11999
AnisotropicDiffusionImageFilter
12001
AnisotropicDiffusionFunction
12003
GradientAnisotropicDiffusionFunction
12005
itk::simple::GradientAnisotropicDiffusion for the procedural interface
12007
itk::GradientAnisotropicDiffusionImageFilter for the Doxygen on the original ITK class.
12010
C++ includes: sitkGradientAnisotropicDiffusionImageFilter.h
12013
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::EstimateOptimalTimeStep "
12015
This method autmatically sets the optimal timestep for an image given
12020
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::Execute "
12022
Execute the filter on the input image
12026
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::Execute "
12028
Execute the filter on the input image with the given parameters
12032
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GetConductanceParameter "
12035
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GetConductanceScalingUpdateInterval "
12038
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GetName "
12044
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GetNumberOfIterations "
12047
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GetTimeStep "
12050
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::GradientAnisotropicDiffusionImageFilter "
12052
Default Constructor that takes no arguments and initializes default
12057
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::SetConductanceParameter "
12060
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::SetConductanceScalingUpdateInterval "
12063
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::SetNumberOfIterations "
12066
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::SetTimeStep "
12069
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::ToString "
12071
Print ourselves out
12075
%feature("docstring") itk::simple::GradientAnisotropicDiffusionImageFilter::~GradientAnisotropicDiffusionImageFilter "
12082
%feature("docstring") itk::simple::GradientImageFilter "
12084
Computes the gradient of an image using directional derivatives.
12087
Computes the gradient of an image using directional derivatives. The
12088
directional derivative at each pixel location is computed by
12089
convolution with a first-order derivative operator.
12091
The second template parameter defines the value type used in the
12092
derivative operator (defaults to float). The third template parameter
12093
defines the value type used for output image (defaults to float). The
12094
output image is defined as a covariant vector image whose value type
12095
is specified as this third template parameter.
12103
NeighborhoodOperator
12105
NeighborhoodIterator
12107
itk::simple::Gradient for the procedural interface
12109
itk::GradientImageFilter for the Doxygen on the original ITK class.
12112
C++ includes: sitkGradientImageFilter.h
12115
%feature("docstring") itk::simple::GradientImageFilter::Execute "
12117
Execute the filter on the input image
12121
%feature("docstring") itk::simple::GradientImageFilter::Execute "
12123
Execute the filter on the input image with the given parameters
12127
%feature("docstring") itk::simple::GradientImageFilter::GetName "
12133
%feature("docstring") itk::simple::GradientImageFilter::GetUseImageDirection "
12135
The UseImageDirection flag determines whether image derivatives are
12136
computed with respect to the image grid or with respect to the
12137
physical space. When this flag is ON the derivatives are computed with
12138
respect to the coordinate system of physical space. The difference is
12139
whether we take into account the image Direction or not. The flag ON
12140
will take into account the image direction and will result in an extra
12141
matrix multiplication compared to the amount of computation performed
12142
when the flag is OFF. The default value of this flag is On.
12146
%feature("docstring") itk::simple::GradientImageFilter::GetUseImageSpacing "
12149
%feature("docstring") itk::simple::GradientImageFilter::GradientImageFilter "
12151
Default Constructor that takes no arguments and initializes default
12156
%feature("docstring") itk::simple::GradientImageFilter::SetUseImageDirection "
12158
The UseImageDirection flag determines whether image derivatives are
12159
computed with respect to the image grid or with respect to the
12160
physical space. When this flag is ON the derivatives are computed with
12161
respect to the coordinate system of physical space. The difference is
12162
whether we take into account the image Direction or not. The flag ON
12163
will take into account the image direction and will result in an extra
12164
matrix multiplication compared to the amount of computation performed
12165
when the flag is OFF. The default value of this flag is On.
12169
%feature("docstring") itk::simple::GradientImageFilter::SetUseImageSpacing "
12171
Set/Get whether or not the filter will use the spacing of the input
12172
image in its calculations
12176
%feature("docstring") itk::simple::GradientImageFilter::ToString "
12178
Print ourselves out
12182
%feature("docstring") itk::simple::GradientImageFilter::UseImageDirectionOff "
12185
%feature("docstring") itk::simple::GradientImageFilter::UseImageDirectionOn "
12187
Set the value of UseImageDirection to true or false respectfully.
12191
%feature("docstring") itk::simple::GradientImageFilter::UseImageSpacingOff "
12194
%feature("docstring") itk::simple::GradientImageFilter::UseImageSpacingOn "
12196
Set the value of UseImageSpacing to true or false respectfully.
12200
%feature("docstring") itk::simple::GradientImageFilter::~GradientImageFilter "
12207
%feature("docstring") itk::simple::GradientMagnitudeImageFilter "
12209
Computes the gradient magnitude of an image region at each pixel.
12218
NeighborhoodOperator
12220
NeighborhoodIterator
12225
Compute the gradient magnitude image
12227
itk::simple::GradientMagnitude for the procedural interface
12229
itk::GradientMagnitudeImageFilter for the Doxygen on the original ITK class.
12233
C++ includes: sitkGradientMagnitudeImageFilter.h
12236
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::Execute "
12238
Execute the filter on the input image
12242
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::Execute "
12244
Execute the filter on the input image with the given parameters
12248
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::GetName "
12254
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::GetUseImageSpacing "
12256
Set/Get whether or not the filter will use the spacing of the input
12257
image in its calculations
12261
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::GradientMagnitudeImageFilter "
12263
Default Constructor that takes no arguments and initializes default
12268
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::SetUseImageSpacing "
12270
Set/Get whether or not the filter will use the spacing of the input
12271
image in its calculations
12275
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::ToString "
12277
Print ourselves out
12281
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::UseImageSpacingOff "
12284
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::UseImageSpacingOn "
12286
Set the value of UseImageSpacing to true or false respectfully.
12290
%feature("docstring") itk::simple::GradientMagnitudeImageFilter::~GradientMagnitudeImageFilter "
12297
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter "
12299
Computes the Magnitude of the Gradient of an image by convolution with
12300
the first derivative of a Gaussian.
12303
This filter is implemented using the recursive gaussian filters
12309
Find the gradient magnitude of the image first smoothed with a
12312
itk::simple::GradientMagnitudeRecursiveGaussian for the procedural interface
12314
itk::GradientMagnitudeRecursiveGaussianImageFilter for the Doxygen on the original ITK class.
12318
C++ includes: sitkGradientMagnitudeRecursiveGaussianImageFilter.h
12321
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::Execute "
12323
Execute the filter on the input image
12327
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::Execute "
12329
Execute the filter on the input image with the given parameters
12333
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::GetName "
12339
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::GetNormalizeAcrossScale "
12341
Define which normalization factor will be used for the Gaussian
12343
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
12348
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::GetSigma "
12350
Set Sigma value. Sigma is measured in the units of image spacing.
12354
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::GradientMagnitudeRecursiveGaussianImageFilter "
12356
Default Constructor that takes no arguments and initializes default
12361
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::NormalizeAcrossScaleOff "
12364
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::NormalizeAcrossScaleOn "
12366
Set the value of NormalizeAcrossScale to true or false respectfully.
12370
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::SetNormalizeAcrossScale "
12372
Define which normalization factor will be used for the Gaussian
12374
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
12379
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::SetSigma "
12381
Set Sigma value. Sigma is measured in the units of image spacing.
12385
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::ToString "
12387
Print ourselves out
12391
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussianImageFilter::~GradientMagnitudeRecursiveGaussianImageFilter "
12398
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter "
12400
Computes the gradient of an image by convolution with the first
12401
derivative of a Gaussian.
12404
This filter is implemented using the recursive gaussian filters.
12406
This filter supports both scalar and vector pixel types within the
12407
input image, including VectorImage type.
12413
Compute the gradient of an image by convolution with the first
12414
derivative of a Gaussian
12416
itk::simple::GradientRecursiveGaussian for the procedural interface
12418
itk::GradientRecursiveGaussianImageFilter for the Doxygen on the original ITK class.
12422
C++ includes: sitkGradientRecursiveGaussianImageFilter.h
12425
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::Execute "
12427
Execute the filter on the input image
12431
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::Execute "
12433
Execute the filter on the input image with the given parameters
12437
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::GetName "
12443
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::GetNormalizeAcrossScale "
12445
Define which normalization factor will be used for the Gaussian
12447
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
12452
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::GetSigma "
12455
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::GetUseImageDirection "
12457
The UseImageDirection flag determines whether the gradients are
12458
computed with respect to the image grid or with respect to the
12459
physical space. When this flag is ON the gradients are computed with
12460
respect to the coordinate system of physical space. The difference is
12461
whether we take into account the image Direction or not. The flag ON
12462
will take into account the image direction and will result in an extra
12463
matrix multiplication compared to the amount of computation performed
12464
when the flag is OFF. The default value of this flag is On.
12468
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::GradientRecursiveGaussianImageFilter "
12470
Default Constructor that takes no arguments and initializes default
12475
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::NormalizeAcrossScaleOff "
12478
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::NormalizeAcrossScaleOn "
12480
Set the value of NormalizeAcrossScale to true or false respectfully.
12484
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::SetNormalizeAcrossScale "
12486
Define which normalization factor will be used for the Gaussian
12488
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
12493
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::SetSigma "
12495
Set Sigma value. Sigma is measured in the units of image spacing.
12499
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::SetUseImageDirection "
12501
The UseImageDirection flag determines whether the gradients are
12502
computed with respect to the image grid or with respect to the
12503
physical space. When this flag is ON the gradients are computed with
12504
respect to the coordinate system of physical space. The difference is
12505
whether we take into account the image Direction or not. The flag ON
12506
will take into account the image direction and will result in an extra
12507
matrix multiplication compared to the amount of computation performed
12508
when the flag is OFF. The default value of this flag is On.
12512
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::ToString "
12514
Print ourselves out
12518
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::UseImageDirectionOff "
12521
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::UseImageDirectionOn "
12523
Set the value of UseImageDirection to true or false respectfully.
12527
%feature("docstring") itk::simple::GradientRecursiveGaussianImageFilter::~GradientRecursiveGaussianImageFilter "
12534
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter "
12536
Enhance pixels associated with a dark object (identified by a seed
12537
pixel) where the dark object is surrounded by a brigher object.
12540
GrayscaleConnectedClosingImagefilter is useful for enhancing dark
12541
objects that are surrounded by bright borders. This filter makes it
12542
easier to threshold the image and extract just the object of interest.
12544
Geodesic morphology and the connected closing algorithm are described
12545
in Chapter 6 of Pierre Soille's book \"Morphological Image Analysis:
12546
Principles and Applications\", Second Edition, Springer, 2003.
12550
GrayscaleGeodesicDilateImageFilter
12552
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
12554
itk::simple::GrayscaleConnectedClosing for the procedural interface
12556
itk::GrayscaleConnectedClosingImageFilter for the Doxygen on the original ITK class.
12559
C++ includes: sitkGrayscaleConnectedClosingImageFilter.h
12562
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::Execute "
12564
Execute the filter on the input image
12568
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::Execute "
12570
Execute the filter on the input image with the given parameters
12574
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::FullyConnectedOff "
12577
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::FullyConnectedOn "
12579
Set the value of FullyConnected to true or false respectfully.
12583
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::GetFullyConnected "
12585
Set/Get whether the connected components are defined strictly by face
12586
connectivity or by face+edge+vertex connectivity. Default is
12587
FullyConnectedOff. For objects that are 1 pixel wide, use
12592
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::GetName "
12598
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::GetSeed "
12600
Set/Get the seed pixel for the segmentation
12604
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::GrayscaleConnectedClosingImageFilter "
12606
Default Constructor that takes no arguments and initializes default
12611
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::SetFullyConnected "
12613
Set/Get whether the connected components are defined strictly by face
12614
connectivity or by face+edge+vertex connectivity. Default is
12615
FullyConnectedOff. For objects that are 1 pixel wide, use
12620
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::SetSeed "
12622
Set/Get the seed pixel for the segmentation
12626
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::ToString "
12628
Print ourselves out
12632
%feature("docstring") itk::simple::GrayscaleConnectedClosingImageFilter::~GrayscaleConnectedClosingImageFilter "
12639
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter "
12641
Enhance pixels associated with a bright object (identified by a seed
12642
pixel) where the bright object is surrounded by a darker object.
12645
GrayscaleConnectedOpeningImagefilter is useful for enhancing bright
12646
objects that are surrounded by dark borders. This filter makes it
12647
easier to threshold the image and extract just the object of interest.
12649
Geodesic morphology and the connected opening algorithm is described
12650
in Chapter 6 of Pierre Soille's book \"Morphological Image Analysis:
12651
Principles and Applications\", Second Edition, Springer, 2003.
12655
GrayscaleGeodesicDilateImageFilter
12657
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
12659
itk::simple::GrayscaleConnectedOpening for the procedural interface
12661
itk::GrayscaleConnectedOpeningImageFilter for the Doxygen on the original ITK class.
12664
C++ includes: sitkGrayscaleConnectedOpeningImageFilter.h
12667
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::Execute "
12669
Execute the filter on the input image
12673
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::Execute "
12675
Execute the filter on the input image with the given parameters
12679
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::FullyConnectedOff "
12682
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::FullyConnectedOn "
12684
Set the value of FullyConnected to true or false respectfully.
12688
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::GetFullyConnected "
12690
Set/Get whether the connected components are defined strictly by face
12691
connectivity or by face+edge+vertex connectivity. Default is
12692
FullyConnectedOff. For objects that are 1 pixel wide, use
12697
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::GetName "
12703
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::GetSeed "
12705
Set/Get the seed pixel for the segmentation
12709
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::GrayscaleConnectedOpeningImageFilter "
12711
Default Constructor that takes no arguments and initializes default
12716
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::SetFullyConnected "
12718
Set/Get whether the connected components are defined strictly by face
12719
connectivity or by face+edge+vertex connectivity. Default is
12720
FullyConnectedOff. For objects that are 1 pixel wide, use
12725
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::SetSeed "
12727
Set/Get the seed pixel for the segmentation
12731
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::ToString "
12733
Print ourselves out
12737
%feature("docstring") itk::simple::GrayscaleConnectedOpeningImageFilter::~GrayscaleConnectedOpeningImageFilter "
12744
%feature("docstring") itk::simple::GrayscaleDilateImageFilter "
12746
Grayscale dilation of an image.
12749
Dilate an image using grayscale morphology. Dilation takes the maximum
12750
of all the pixels identified by the structuring element.
12752
The structuring element is assumed to be composed of binary values
12753
(zero or one). Only elements of the structuring element having values
12754
> 0 are candidates for affecting the center pixel.
12758
MorphologyImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
12763
Dilate a grayscale image
12765
itk::simple::GrayscaleDilate for the procedural interface
12767
itk::GrayscaleDilateImageFilter for the Doxygen on the original ITK class.
12771
C++ includes: sitkGrayscaleDilateImageFilter.h
12774
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::Execute "
12776
Execute the filter on the input image
12780
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::GetKernelRadius "
12783
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::GetKernelType "
12786
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::GetName "
12792
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::GrayscaleDilateImageFilter "
12794
Default Constructor that takes no arguments and initializes default
12799
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::SetKernelRadius "
12801
Kernel radius as a scale for isotropic structures
12805
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::SetKernelRadius "
12807
Set/Get the radius of the kernel structuring element as a vector.
12809
If the dimension of the image is greater then the length of r, then
12810
the radius will be padded. If it is less the r will be truncated.
12814
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::SetKernelType "
12816
Set/Get the kernel or structuring elemenent used for the morphology
12820
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::SetKernelType "
12823
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::ToString "
12825
Print ourselves out
12829
%feature("docstring") itk::simple::GrayscaleDilateImageFilter::~GrayscaleDilateImageFilter "
12836
%feature("docstring") itk::simple::GrayscaleErodeImageFilter "
12838
Grayscale erosion of an image.
12841
Erode an image using grayscale morphology. Erosion takes the maximum
12842
of all the pixels identified by the structuring element.
12844
The structuring element is assumed to be composed of binary values
12845
(zero or one). Only elements of the structuring element having values
12846
> 0 are candidates for affecting the center pixel.
12850
MorphologyImageFilter , GrayscaleFunctionErodeImageFilter , BinaryErodeImageFilter
12855
Erode a grayscale image
12857
itk::simple::GrayscaleErode for the procedural interface
12859
itk::GrayscaleErodeImageFilter for the Doxygen on the original ITK class.
12863
C++ includes: sitkGrayscaleErodeImageFilter.h
12866
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::Execute "
12868
Execute the filter on the input image
12872
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::GetKernelRadius "
12875
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::GetKernelType "
12878
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::GetName "
12884
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::GrayscaleErodeImageFilter "
12886
Default Constructor that takes no arguments and initializes default
12891
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::SetKernelRadius "
12893
Kernel radius as a scale for isotropic structures
12897
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::SetKernelRadius "
12899
Set/Get the radius of the kernel structuring element as a vector.
12901
If the dimension of the image is greater then the length of r, then
12902
the radius will be padded. If it is less the r will be truncated.
12906
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::SetKernelType "
12908
Set/Get the kernel or structuring elemenent used for the morphology
12912
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::SetKernelType "
12915
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::ToString "
12917
Print ourselves out
12921
%feature("docstring") itk::simple::GrayscaleErodeImageFilter::~GrayscaleErodeImageFilter "
12928
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter "
12930
Remove local minima not connected to the boundary of the image.
12933
GrayscaleFillholeImageFilter fills holes in a grayscale image. Holes are local minima in the
12934
grayscale topography that are not connected to boundaries of the
12935
image. Gray level values adjacent to a hole are extrapolated across
12938
This filter is used to smooth over local minima without affecting the
12939
values of local maxima. If you take the difference between the output
12940
of this filter and the original image (and perhaps threshold the
12941
difference above a small value), you'll obtain a map of the local
12944
This filter uses the ReconstructionByErosionImageFilter . It provides its own input as the \"mask\" input to the geodesic
12945
erosion. The \"marker\" image for the geodesic erosion is constructed
12946
such that boundary pixels match the boundary pixels of the input image
12947
and the interior pixels are set to the maximum pixel value in the
12950
Geodesic morphology and the Fillhole algorithm is described in Chapter
12951
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
12952
and Applications\", Second Edition, Springer, 2003.
12956
ReconstructionByErosionImageFilter
12958
MorphologyImageFilter , GrayscaleErodeImageFilter , GrayscaleFunctionErodeImageFilter , BinaryErodeImageFilter
12960
itk::simple::GrayscaleFillhole for the procedural interface
12962
itk::GrayscaleFillholeImageFilter for the Doxygen on the original ITK class.
12965
C++ includes: sitkGrayscaleFillholeImageFilter.h
12968
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::Execute "
12970
Execute the filter on the input image
12974
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::Execute "
12976
Execute the filter on the input image with the given parameters
12980
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::FullyConnectedOff "
12983
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::FullyConnectedOn "
12985
Set the value of FullyConnected to true or false respectfully.
12989
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::GetFullyConnected "
12991
Set/Get whether the connected components are defined strictly by face
12992
connectivity or by face+edge+vertex connectivity. Default is
12993
FullyConnectedOff. For objects that are 1 pixel wide, use
12998
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::GetName "
13004
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::GrayscaleFillholeImageFilter "
13006
Default Constructor that takes no arguments and initializes default
13011
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::SetFullyConnected "
13013
Set/Get whether the connected components are defined strictly by face
13014
connectivity or by face+edge+vertex connectivity. Default is
13015
FullyConnectedOff. For objects that are 1 pixel wide, use
13020
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::ToString "
13022
Print ourselves out
13026
%feature("docstring") itk::simple::GrayscaleFillholeImageFilter::~GrayscaleFillholeImageFilter "
13033
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter "
13035
geodesic gray scale dilation of an image
13038
Geodesic dilation operates on a \"marker\" image and a \"mask\" image.
13039
The marker image is dilated using an elementary structuring element
13040
(neighborhood of radius one using only the face connected neighbors).
13041
The resulting image is then compared with the mask image. The output
13042
image is the pixelwise minimum of the dilated marker image and the
13045
Geodesic dilation is run either one iteration or until convergence. In
13046
the convergence case, the filter is equivalent to \"reconstruction by
13047
dilation\". This filter is implemented to handle both scenarios. The
13048
one iteration case is multi-threaded. The convergence case is
13049
delegated to another instance of the same filter (but configured to
13050
run a single iteration).
13052
The marker image must be less than or equal to the mask image (on a
13053
pixel by pixel basis).
13055
Geodesic morphology is described in Chapter 6 of Pierre Soille's book
13056
\"Morphological Image Analysis: Principles and Applications\", Second
13057
Edition, Springer, 2003.
13059
A noniterative version of this algorithm can be found in the ReconstructionByDilationImageFilter . This noniterative solution is much faster than the implementation
13060
provided here. All ITK filters that previously used
13061
GrayscaleGeodesicDiliateImageFilter as part of their implementation
13062
have been converted to use the ReconstructionByDilationImageFilter . The GrayscaleGeodesicDilateImageFilter is maintained for backward compatibility.
13066
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter , ReconstructionByDilationImageFilter
13068
itk::simple::GrayscaleGeodesicDilate for the procedural interface
13070
itk::GrayscaleGeodesicDilateImageFilter for the Doxygen on the original ITK class.
13073
C++ includes: sitkGrayscaleGeodesicDilateImageFilter.h
13076
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::Execute "
13078
Execute the filter on the input images
13082
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::Execute "
13084
Execute the filter on the input images with the given parameters
13088
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::FullyConnectedOff "
13091
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::FullyConnectedOn "
13093
Set the value of FullyConnected to true or false respectfully.
13097
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::GetFullyConnected "
13099
Set/Get whether the connected components are defined strictly by face
13100
connectivity or by face+edge+vertex connectivity. Default is
13101
FullyConnectedOff. For objects that are 1 pixel wide, use
13106
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::GetName "
13112
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::GetRunOneIteration "
13114
Set/Get whether the filter should run one iteration or until
13115
convergence. When run to convergence, this filter is equivalent to
13116
\"reconstruction by dilation\". Default is off.
13120
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::GrayscaleGeodesicDilateImageFilter "
13122
Default Constructor that takes no arguments and initializes default
13127
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::RunOneIterationOff "
13130
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::RunOneIterationOn "
13132
Set the value of RunOneIteration to true or false respectfully.
13136
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::SetFullyConnected "
13138
Set/Get whether the connected components are defined strictly by face
13139
connectivity or by face+edge+vertex connectivity. Default is
13140
FullyConnectedOff. For objects that are 1 pixel wide, use
13145
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::SetRunOneIteration "
13147
Set/Get whether the filter should run one iteration or until
13148
convergence. When run to convergence, this filter is equivalent to
13149
\"reconstruction by dilation\". Default is off.
13153
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::ToString "
13155
Print ourselves out
13159
%feature("docstring") itk::simple::GrayscaleGeodesicDilateImageFilter::~GrayscaleGeodesicDilateImageFilter "
13166
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter "
13168
geodesic gray scale erosion of an image
13171
Geodesic erosion operates on a \"marker\" image and a \"mask\" image.
13172
The marker image is eroded using an elementary structuring element
13173
(neighborhood of radius one using only the face connected neighbors).
13174
The resulting image is then compared with the mask image. The output
13175
image is the pixelwise maximum of the eroded marker image and the mask
13178
Geodesic erosion is run either one iteration or until convergence. In
13179
the convergence case, the filter is equivalent to \"reconstruction by
13180
erosion\". This filter is implemented to handle both scenarios. The
13181
one iteration case is multi-threaded. The convergence case is
13182
delegated to another instance of the same filter (but configured to
13183
run a single iteration).
13185
The marker image must be greater than or equal to the mask image (on a
13186
pixel by pixel basis).
13188
Geodesic morphology is described in Chapter 6 of Pierre Soille's book
13189
\"Morphological Image Analysis: Principles and Applications\", Second
13190
Edition, Springer, 2003.
13192
A noniterative version of this algorithm can be found in the ReconstructionByErosionImageFilter . This noniterative solution is much faster than the implementation
13193
provided here. All ITK filters that previously used GrayscaleGeodesicErodeImageFilter as part of their implementation have been converted to use the ReconstructionByErosionImageFilter . The GrayscaleGeodesicErodeImageFilter is maintained for backward compatibility.
13197
MorphologyImageFilter , GrayscaleErodeImageFilter , GrayscaleFunctionErodeImageFilter , BinaryErodeImageFilter , ReconstructionByErosionImageFilter
13199
itk::simple::GrayscaleGeodesicErode for the procedural interface
13201
itk::GrayscaleGeodesicErodeImageFilter for the Doxygen on the original ITK class.
13204
C++ includes: sitkGrayscaleGeodesicErodeImageFilter.h
13207
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::Execute "
13209
Execute the filter on the input images
13213
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::Execute "
13215
Execute the filter on the input images with the given parameters
13219
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::FullyConnectedOff "
13222
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::FullyConnectedOn "
13224
Set the value of FullyConnected to true or false respectfully.
13228
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::GetFullyConnected "
13230
Set/Get whether the connected components are defined strictly by face
13231
connectivity or by face+edge+vertex connectivity. Default is
13232
FullyConnectedOff. For objects that are 1 pixel wide, use
13237
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::GetName "
13243
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::GetRunOneIteration "
13245
Set/Get whether the filter should run one iteration or until
13246
convergence. When run to convergence, this filter is equivalent to
13247
\"reconstruction by erosion\". Default is off.
13251
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::GrayscaleGeodesicErodeImageFilter "
13253
Default Constructor that takes no arguments and initializes default
13258
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::RunOneIterationOff "
13261
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::RunOneIterationOn "
13263
Set the value of RunOneIteration to true or false respectfully.
13267
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::SetFullyConnected "
13269
Set/Get whether the connected components are defined strictly by face
13270
connectivity or by face+edge+vertex connectivity. Default is
13271
FullyConnectedOff. For objects that are 1 pixel wide, use
13276
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::SetRunOneIteration "
13278
Set/Get whether the filter should run one iteration or until
13279
convergence. When run to convergence, this filter is equivalent to
13280
\"reconstruction by erosion\". Default is off.
13284
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::ToString "
13286
Print ourselves out
13290
%feature("docstring") itk::simple::GrayscaleGeodesicErodeImageFilter::~GrayscaleGeodesicErodeImageFilter "
13297
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter "
13299
Remove local maxima not connected to the boundary of the image.
13302
GrayscaleGrindPeakImageFilter removes peaks in a grayscale image. Peaks are local maxima in the
13303
grayscale topography that are not connected to boundaries of the
13304
image. Gray level values adjacent to a peak are extrapolated through
13307
This filter is used to smooth over local maxima without affecting the
13308
values of local minima. If you take the difference between the output
13309
of this filter and the original image (and perhaps threshold the
13310
difference above a small value), you'll obtain a map of the local
13313
This filter uses the GrayscaleGeodesicDilateImageFilter . It provides its own input as the \"mask\" input to the geodesic
13314
erosion. The \"marker\" image for the geodesic erosion is constructed
13315
such that boundary pixels match the boundary pixels of the input image
13316
and the interior pixels are set to the minimum pixel value in the
13319
This filter is the dual to the GrayscaleFillholeImageFilter which implements the Fillhole algorithm. Since it is a dual, it is
13320
somewhat superfluous but is provided as a convenience.
13322
Geodesic morphology and the Fillhole algorithm is described in Chapter
13323
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
13324
and Applications\", Second Edition, Springer, 2003.
13328
GrayscaleGeodesicDilateImageFilter
13330
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
13332
itk::simple::GrayscaleGrindPeak for the procedural interface
13334
itk::GrayscaleGrindPeakImageFilter for the Doxygen on the original ITK class.
13337
C++ includes: sitkGrayscaleGrindPeakImageFilter.h
13340
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::Execute "
13342
Execute the filter on the input image
13346
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::Execute "
13348
Execute the filter on the input image with the given parameters
13352
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::FullyConnectedOff "
13355
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::FullyConnectedOn "
13357
Set the value of FullyConnected to true or false respectfully.
13361
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::GetFullyConnected "
13363
Set/Get whether the connected components are defined strictly by face
13364
connectivity or by face+edge+vertex connectivity. Default is
13365
FullyConnectedOff. For objects that are 1 pixel wide, use
13370
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::GetName "
13376
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::GrayscaleGrindPeakImageFilter "
13378
Default Constructor that takes no arguments and initializes default
13383
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::SetFullyConnected "
13385
Set/Get whether the connected components are defined strictly by face
13386
connectivity or by face+edge+vertex connectivity. Default is
13387
FullyConnectedOff. For objects that are 1 pixel wide, use
13392
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::ToString "
13394
Print ourselves out
13398
%feature("docstring") itk::simple::GrayscaleGrindPeakImageFilter::~GrayscaleGrindPeakImageFilter "
13405
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter "
13407
gray scale dilation of an image
13410
Erode an image using grayscale morphology. Dilation takes the maximum
13411
of all the pixels identified by the structuring element.
13413
The structuring element is assumed to be composed of binary values
13414
(zero or one). Only elements of the structuring element having values
13415
> 0 are candidates for affecting the center pixel.
13419
MorphologyImageFilter , GrayscaleFunctionErodeImageFilter , BinaryErodeImageFilter
13421
itk::simple::GrayscaleMorphologicalClosing for the procedural interface
13423
itk::GrayscaleMorphologicalClosingImageFilter for the Doxygen on the original ITK class.
13426
C++ includes: sitkGrayscaleMorphologicalClosingImageFilter.h
13429
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::Execute "
13431
Execute the filter on the input image
13435
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::Execute "
13437
Execute the filter on the input image with the given parameters
13441
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::GetKernelRadius "
13444
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::GetKernelType "
13447
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::GetName "
13453
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::GetSafeBorder "
13455
A safe border is added to input image to avoid borders effects and
13456
remove it once the closing is done
13460
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::GrayscaleMorphologicalClosingImageFilter "
13462
Default Constructor that takes no arguments and initializes default
13467
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SafeBorderOff "
13470
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SafeBorderOn "
13472
Set the value of SafeBorder to true or false respectfully.
13476
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SetKernelRadius "
13478
Kernel radius as a scale for isotropic structures
13482
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SetKernelRadius "
13484
Set/Get the radius of the kernel structuring element as a vector.
13486
If the dimension of the image is greater then the length of r, then
13487
the radius will be padded. If it is less the r will be truncated.
13491
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SetKernelType "
13493
Set/Get the kernel or structuring elemenent used for the morphology
13497
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SetKernelType "
13500
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::SetSafeBorder "
13502
A safe border is added to input image to avoid borders effects and
13503
remove it once the closing is done
13507
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::ToString "
13509
Print ourselves out
13513
%feature("docstring") itk::simple::GrayscaleMorphologicalClosingImageFilter::~GrayscaleMorphologicalClosingImageFilter "
13520
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter "
13522
gray scale dilation of an image
13525
Dilate an image using grayscale morphology. Dilation takes the maximum
13526
of all the pixels identified by the structuring element.
13528
The structuring element is assumed to be composed of binary values
13529
(zero or one). Only elements of the structuring element having values
13530
> 0 are candidates for affecting the center pixel.
13534
MorphologyImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
13536
itk::simple::GrayscaleMorphologicalOpening for the procedural interface
13538
itk::GrayscaleMorphologicalOpeningImageFilter for the Doxygen on the original ITK class.
13541
C++ includes: sitkGrayscaleMorphologicalOpeningImageFilter.h
13544
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::Execute "
13546
Execute the filter on the input image
13550
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::Execute "
13552
Execute the filter on the input image with the given parameters
13556
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::GetKernelRadius "
13559
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::GetKernelType "
13562
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::GetName "
13568
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::GetSafeBorder "
13570
A safe border is added to input image to avoid borders effects and
13571
remove it once the closing is done
13575
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::GrayscaleMorphologicalOpeningImageFilter "
13577
Default Constructor that takes no arguments and initializes default
13582
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SafeBorderOff "
13585
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SafeBorderOn "
13587
Set the value of SafeBorder to true or false respectfully.
13591
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SetKernelRadius "
13593
Kernel radius as a scale for isotropic structures
13597
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SetKernelRadius "
13599
Set/Get the radius of the kernel structuring element as a vector.
13601
If the dimension of the image is greater then the length of r, then
13602
the radius will be padded. If it is less the r will be truncated.
13606
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SetKernelType "
13608
Set/Get the kernel or structuring elemenent used for the morphology
13612
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SetKernelType "
13615
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::SetSafeBorder "
13617
A safe border is added to input image to avoid borders effects and
13618
remove it once the closing is done
13622
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::ToString "
13624
Print ourselves out
13628
%feature("docstring") itk::simple::GrayscaleMorphologicalOpeningImageFilter::~GrayscaleMorphologicalOpeningImageFilter "
13635
%feature("docstring") itk::simple::GreaterEqualImageFilter "
13637
Implements pixel-wise generic operation of two images, or of an image
13641
This class is parameterized over the types of the two input images and
13642
the type of the output image. It is also parameterized by the
13643
operation to be applied. A Functor style is used.
13645
The constant must be of the same type than the pixel type of the
13646
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
13647
GetConstant() methods are provided as shortcuts to set or get the
13648
constant value without manipulating the decorator.
13652
UnaryFunctorImageFilter TernaryFunctorImageFilter
13657
Apply a predefined operation to corresponding pixels in two images
13659
Apply a custom operation to corresponding pixels in two images
13661
itk::simple::GreaterEqual for the procedural interface
13663
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
13667
C++ includes: sitkGreaterEqualImageFilter.h
13670
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13672
Execute the filter on the input images
13676
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13678
Execute the filter on the input images with the given parameters
13682
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13684
Execute the filter with an image and a constant
13688
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13691
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13693
Execute the filter on an image and a constant with the given
13698
%feature("docstring") itk::simple::GreaterEqualImageFilter::Execute "
13701
%feature("docstring") itk::simple::GreaterEqualImageFilter::GetBackgroundValue "
13703
Set/Get the value used to mark the false pixels of the operator.
13707
%feature("docstring") itk::simple::GreaterEqualImageFilter::GetForegroundValue "
13709
Set/Get the value used to mark the true pixels of the operator.
13713
%feature("docstring") itk::simple::GreaterEqualImageFilter::GetName "
13719
%feature("docstring") itk::simple::GreaterEqualImageFilter::GreaterEqualImageFilter "
13721
Default Constructor that takes no arguments and initializes default
13726
%feature("docstring") itk::simple::GreaterEqualImageFilter::SetBackgroundValue "
13728
Set/Get the value used to mark the false pixels of the operator.
13732
%feature("docstring") itk::simple::GreaterEqualImageFilter::SetForegroundValue "
13734
Set/Get the value used to mark the true pixels of the operator.
13738
%feature("docstring") itk::simple::GreaterEqualImageFilter::ToString "
13740
Print ourselves out
13744
%feature("docstring") itk::simple::GreaterEqualImageFilter::~GreaterEqualImageFilter "
13751
%feature("docstring") itk::simple::GreaterImageFilter "
13753
Implements pixel-wise generic operation of two images, or of an image
13757
This class is parameterized over the types of the two input images and
13758
the type of the output image. It is also parameterized by the
13759
operation to be applied. A Functor style is used.
13761
The constant must be of the same type than the pixel type of the
13762
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
13763
GetConstant() methods are provided as shortcuts to set or get the
13764
constant value without manipulating the decorator.
13768
UnaryFunctorImageFilter TernaryFunctorImageFilter
13773
Apply a predefined operation to corresponding pixels in two images
13775
Apply a custom operation to corresponding pixels in two images
13777
itk::simple::Greater for the procedural interface
13779
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
13783
C++ includes: sitkGreaterImageFilter.h
13786
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13788
Execute the filter on the input images
13792
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13794
Execute the filter on the input images with the given parameters
13798
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13800
Execute the filter with an image and a constant
13804
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13807
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13809
Execute the filter on an image and a constant with the given
13814
%feature("docstring") itk::simple::GreaterImageFilter::Execute "
13817
%feature("docstring") itk::simple::GreaterImageFilter::GetBackgroundValue "
13819
Set/Get the value used to mark the false pixels of the operator.
13823
%feature("docstring") itk::simple::GreaterImageFilter::GetForegroundValue "
13825
Set/Get the value used to mark the true pixels of the operator.
13829
%feature("docstring") itk::simple::GreaterImageFilter::GetName "
13835
%feature("docstring") itk::simple::GreaterImageFilter::GreaterImageFilter "
13837
Default Constructor that takes no arguments and initializes default
13842
%feature("docstring") itk::simple::GreaterImageFilter::SetBackgroundValue "
13844
Set/Get the value used to mark the false pixels of the operator.
13848
%feature("docstring") itk::simple::GreaterImageFilter::SetForegroundValue "
13850
Set/Get the value used to mark the true pixels of the operator.
13854
%feature("docstring") itk::simple::GreaterImageFilter::ToString "
13856
Print ourselves out
13860
%feature("docstring") itk::simple::GreaterImageFilter::~GreaterImageFilter "
13867
%feature("docstring") itk::simple::GridImageSource "
13869
Generate an n-dimensional image of a grid.
13872
GridImageSource generates an image of a grid. From the abstract... \"Certain classes
13873
of images find disparate use amongst members of the ITK community for
13874
such purposes as visualization, simulation, testing, etc. Currently
13875
there exists two derived classes from the ImageSource class used for
13876
generating specific images for various applications, viz.
13877
RandomImageSource and GaussianImageSource . We propose to add to this
13878
set with the class GridImageSource which, obviously enough, produces a
13879
grid image. Such images are useful for visualizing deformation when
13880
used in conjunction with the WarpImageFilter , simulating magnetic
13881
resonance tagging images, or creating optical illusions with which to
13882
amaze your friends.\"
13884
The output image may be of any dimension.
13887
Tustison N., Avants B., Gee J. University of Pennsylvania
13888
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/475
13890
itk::simple::GridImageSource for the procedural interface
13892
itk::GridImageSource for the Doxygen on the original ITK class.
13895
C++ includes: sitkGridImageSource.h
13898
%feature("docstring") itk::simple::GridImageSource::Execute "
13900
Execute the filter on the input image
13904
%feature("docstring") itk::simple::GridImageSource::Execute "
13906
Execute the filter on the input image with the given parameters
13910
%feature("docstring") itk::simple::GridImageSource::GetDirection "
13913
%feature("docstring") itk::simple::GridImageSource::GetGridOffset "
13915
Set/Get the grid offset.
13919
%feature("docstring") itk::simple::GridImageSource::GetGridSpacing "
13921
Set/Get the grid spacing of the peaks.
13925
%feature("docstring") itk::simple::GridImageSource::GetName "
13931
%feature("docstring") itk::simple::GridImageSource::GetOrigin "
13934
%feature("docstring") itk::simple::GridImageSource::GetOutputPixelType "
13937
%feature("docstring") itk::simple::GridImageSource::GetScale "
13939
Set/Get the scale factor to multiply the true value of the grid.
13943
%feature("docstring") itk::simple::GridImageSource::GetSigma "
13945
Set/Get the standard deviation of the Gaussians or width of the box
13950
%feature("docstring") itk::simple::GridImageSource::GetSize "
13953
%feature("docstring") itk::simple::GridImageSource::GetSpacing "
13956
%feature("docstring") itk::simple::GridImageSource::GridImageSource "
13958
Default Constructor that takes no arguments and initializes default
13963
%feature("docstring") itk::simple::GridImageSource::SetDirection "
13966
%feature("docstring") itk::simple::GridImageSource::SetGridOffset "
13968
Set/Get the grid offset.
13972
%feature("docstring") itk::simple::GridImageSource::SetGridSpacing "
13974
Set/Get the grid spacing of the peaks.
13978
%feature("docstring") itk::simple::GridImageSource::SetOrigin "
13981
%feature("docstring") itk::simple::GridImageSource::SetOutputPixelType "
13984
%feature("docstring") itk::simple::GridImageSource::SetScale "
13986
Set/Get the scale factor to multiply the true value of the grid.
13990
%feature("docstring") itk::simple::GridImageSource::SetSigma "
13992
Set/Get the standard deviation of the Gaussians or width of the box
13997
%feature("docstring") itk::simple::GridImageSource::SetSigma "
13999
Set the values of the Sigma vector all to value
14003
%feature("docstring") itk::simple::GridImageSource::SetSize "
14006
%feature("docstring") itk::simple::GridImageSource::SetSpacing "
14009
%feature("docstring") itk::simple::GridImageSource::ToString "
14011
Print ourselves out
14015
%feature("docstring") itk::simple::GridImageSource::~GridImageSource "
14022
%feature("docstring") itk::simple::HConcaveImageFilter "
14024
Identify local minima whose depth below the baseline is greater than
14028
HConcaveImageFilter extract local minima that are more than h intensity units below the
14029
(local) background. This has the effect of extracting objects that are
14030
darker than the background by at least h intensity units.
14032
This filter uses the HMinimaImageFilter .
14034
Geodesic morphology and the H-Convex algorithm is described in Chapter
14035
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
14036
and Applications\", Second Edition, Springer, 2003.
14040
GrayscaleGeodesicDilateImageFilter , HMaximaImageFilter ,
14042
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
14044
itk::simple::HConcave for the procedural interface
14046
itk::HConcaveImageFilter for the Doxygen on the original ITK class.
14049
C++ includes: sitkHConcaveImageFilter.h
14052
%feature("docstring") itk::simple::HConcaveImageFilter::Execute "
14054
Execute the filter on the input image
14058
%feature("docstring") itk::simple::HConcaveImageFilter::Execute "
14060
Execute the filter on the input image with the given parameters
14064
%feature("docstring") itk::simple::HConcaveImageFilter::FullyConnectedOff "
14067
%feature("docstring") itk::simple::HConcaveImageFilter::FullyConnectedOn "
14069
Set the value of FullyConnected to true or false respectfully.
14073
%feature("docstring") itk::simple::HConcaveImageFilter::GetFullyConnected "
14075
Set/Get whether the connected components are defined strictly by face
14076
connectivity or by face+edge+vertex connectivity. Default is
14077
FullyConnectedOff. For objects that are 1 pixel wide, use
14082
%feature("docstring") itk::simple::HConcaveImageFilter::GetHeight "
14084
Set/Get the height that a local maximum must be above the local
14085
background (local contrast) in order to survive the processing. Local
14086
maxima below this value are replaced with an estimate of the local
14091
%feature("docstring") itk::simple::HConcaveImageFilter::GetName "
14097
%feature("docstring") itk::simple::HConcaveImageFilter::HConcaveImageFilter "
14099
Default Constructor that takes no arguments and initializes default
14104
%feature("docstring") itk::simple::HConcaveImageFilter::SetFullyConnected "
14106
Set/Get whether the connected components are defined strictly by face
14107
connectivity or by face+edge+vertex connectivity. Default is
14108
FullyConnectedOff. For objects that are 1 pixel wide, use
14113
%feature("docstring") itk::simple::HConcaveImageFilter::SetHeight "
14115
Set/Get the height that a local maximum must be above the local
14116
background (local contrast) in order to survive the processing. Local
14117
maxima below this value are replaced with an estimate of the local
14122
%feature("docstring") itk::simple::HConcaveImageFilter::ToString "
14124
Print ourselves out
14128
%feature("docstring") itk::simple::HConcaveImageFilter::~HConcaveImageFilter "
14135
%feature("docstring") itk::simple::HConvexImageFilter "
14137
Identify local maxima whose height above the baseline is greater than
14141
HConvexImageFilter extract local maxima that are more than h intensity units above the
14142
(local) background. This has the effect of extracting objects that are
14143
brighter than background by at least h intensity units.
14145
This filter uses the HMaximaImageFilter .
14147
Geodesic morphology and the H-Convex algorithm is described in Chapter
14148
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
14149
and Applications\", Second Edition, Springer, 2003.
14153
GrayscaleGeodesicDilateImageFilter , HMinimaImageFilter
14155
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
14157
itk::simple::HConvex for the procedural interface
14159
itk::HConvexImageFilter for the Doxygen on the original ITK class.
14162
C++ includes: sitkHConvexImageFilter.h
14165
%feature("docstring") itk::simple::HConvexImageFilter::Execute "
14167
Execute the filter on the input image
14171
%feature("docstring") itk::simple::HConvexImageFilter::Execute "
14173
Execute the filter on the input image with the given parameters
14177
%feature("docstring") itk::simple::HConvexImageFilter::FullyConnectedOff "
14180
%feature("docstring") itk::simple::HConvexImageFilter::FullyConnectedOn "
14182
Set the value of FullyConnected to true or false respectfully.
14186
%feature("docstring") itk::simple::HConvexImageFilter::GetFullyConnected "
14188
Set/Get whether the connected components are defined strictly by face
14189
connectivity or by face+edge+vertex connectivity. Default is
14190
FullyConnectedOff. For objects that are 1 pixel wide, use
14195
%feature("docstring") itk::simple::HConvexImageFilter::GetHeight "
14197
Set/Get the height that a local maximum must be above the local
14198
background (local contrast) in order to survive the processing. Local
14199
maxima below this value are replaced with an estimate of the local
14204
%feature("docstring") itk::simple::HConvexImageFilter::GetName "
14210
%feature("docstring") itk::simple::HConvexImageFilter::HConvexImageFilter "
14212
Default Constructor that takes no arguments and initializes default
14217
%feature("docstring") itk::simple::HConvexImageFilter::SetFullyConnected "
14219
Set/Get whether the connected components are defined strictly by face
14220
connectivity or by face+edge+vertex connectivity. Default is
14221
FullyConnectedOff. For objects that are 1 pixel wide, use
14226
%feature("docstring") itk::simple::HConvexImageFilter::SetHeight "
14228
Set/Get the height that a local maximum must be above the local
14229
background (local contrast) in order to survive the processing. Local
14230
maxima below this value are replaced with an estimate of the local
14235
%feature("docstring") itk::simple::HConvexImageFilter::ToString "
14237
Print ourselves out
14241
%feature("docstring") itk::simple::HConvexImageFilter::~HConvexImageFilter "
14248
%feature("docstring") itk::simple::HMaximaImageFilter "
14250
Suppress local maxima whose height above the baseline is less than h.
14253
HMaximaImageFilter suppresses local maxima that are less than h intensity units above
14254
the (local) background. This has the effect of smoothing over the
14255
\"high\" parts of the noise in the image without smoothing over large
14256
changes in intensity (region boundaries). See the HMinimaImageFilter to suppress the local minima whose depth is less than h intensity
14257
units below the (local) background.
14259
If the output of HMaximaImageFilter is subtracted from the original image, the signicant \"peaks\" in the
14260
image can be identified. This is what the HConvexImageFilter provides.
14262
This filter uses the ReconstructionByDilationImageFilter . It provides its own input as the \"mask\" input to the geodesic
14263
dilation. The \"marker\" image for the geodesic dilation is the input
14264
image minus the height parameter h.
14266
Geodesic morphology and the H-Maxima algorithm is described in Chapter
14267
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
14268
and Applications\", Second Edition, Springer, 2003.
14270
The height parameter is set using SetHeight.
14274
ReconstructionByDilationImageFilter , HMinimaImageFilter , HConvexImageFilter
14276
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
14278
itk::simple::HMaxima for the procedural interface
14280
itk::HMaximaImageFilter for the Doxygen on the original ITK class.
14283
C++ includes: sitkHMaximaImageFilter.h
14286
%feature("docstring") itk::simple::HMaximaImageFilter::Execute "
14288
Execute the filter on the input image
14292
%feature("docstring") itk::simple::HMaximaImageFilter::Execute "
14294
Execute the filter on the input image with the given parameters
14298
%feature("docstring") itk::simple::HMaximaImageFilter::GetHeight "
14300
Set/Get the height that a local maximum must be above the local
14301
background (local contrast) in order to survive the processing. Local
14302
maxima below this value are replaced with an estimate of the local
14307
%feature("docstring") itk::simple::HMaximaImageFilter::GetName "
14313
%feature("docstring") itk::simple::HMaximaImageFilter::HMaximaImageFilter "
14315
Default Constructor that takes no arguments and initializes default
14320
%feature("docstring") itk::simple::HMaximaImageFilter::SetHeight "
14322
Set/Get the height that a local maximum must be above the local
14323
background (local contrast) in order to survive the processing. Local
14324
maxima below this value are replaced with an estimate of the local
14329
%feature("docstring") itk::simple::HMaximaImageFilter::ToString "
14331
Print ourselves out
14335
%feature("docstring") itk::simple::HMaximaImageFilter::~HMaximaImageFilter "
14342
%feature("docstring") itk::simple::HMinimaImageFilter "
14344
Suppress local minima whose depth below the baseline is less than h.
14347
HMinimaImageFilter suppresses local minima that are less than h intensity units below
14348
the (local) background. This has the effect of smoothing over the
14349
\"low\" parts of the noise in the image without smoothing over large
14350
changes in intensity (region boundaries). See the HMaximaImageFilter to suppress the local maxima whose height is less than h intensity
14351
units above the (local) background.
14353
If original image is subtracted from the output of HMinimaImageFilter , the signicant \"valleys\" in the image can be identified. This is
14354
what the HConcaveImageFilter provides.
14356
This filter uses the GrayscaleGeodesicErodeImageFilter . It provides its own input as the \"mask\" input to the geodesic
14357
dilation. The \"marker\" image for the geodesic dilation is the input
14358
image plus the height parameter h.
14360
Geodesic morphology and the H-Minima algorithm is described in Chapter
14361
6 of Pierre Soille's book \"Morphological Image Analysis: Principles
14362
and Applications\", Second Edition, Springer, 2003.
14366
GrayscaleGeodesicDilateImageFilter , HMinimaImageFilter , HConvexImageFilter
14368
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
14370
itk::simple::HMinima for the procedural interface
14372
itk::HMinimaImageFilter for the Doxygen on the original ITK class.
14375
C++ includes: sitkHMinimaImageFilter.h
14378
%feature("docstring") itk::simple::HMinimaImageFilter::Execute "
14380
Execute the filter on the input image
14384
%feature("docstring") itk::simple::HMinimaImageFilter::Execute "
14386
Execute the filter on the input image with the given parameters
14390
%feature("docstring") itk::simple::HMinimaImageFilter::FullyConnectedOff "
14393
%feature("docstring") itk::simple::HMinimaImageFilter::FullyConnectedOn "
14395
Set the value of FullyConnected to true or false respectfully.
14399
%feature("docstring") itk::simple::HMinimaImageFilter::GetFullyConnected "
14401
Set/Get whether the connected components are defined strictly by face
14402
connectivity or by face+edge+vertex connectivity. Default is
14403
FullyConnectedOff. For objects that are 1 pixel wide, use
14408
%feature("docstring") itk::simple::HMinimaImageFilter::GetHeight "
14410
Set/Get the height that a local maximum must be above the local
14411
background (local contrast) in order to survive the processing. Local
14412
maxima below this value are replaced with an estimate of the local
14417
%feature("docstring") itk::simple::HMinimaImageFilter::GetName "
14423
%feature("docstring") itk::simple::HMinimaImageFilter::HMinimaImageFilter "
14425
Default Constructor that takes no arguments and initializes default
14430
%feature("docstring") itk::simple::HMinimaImageFilter::SetFullyConnected "
14432
Set/Get whether the connected components are defined strictly by face
14433
connectivity or by face+edge+vertex connectivity. Default is
14434
FullyConnectedOff. For objects that are 1 pixel wide, use
14439
%feature("docstring") itk::simple::HMinimaImageFilter::SetHeight "
14441
Set/Get the height that a local maximum must be above the local
14442
background (local contrast) in order to survive the processing. Local
14443
maxima below this value are replaced with an estimate of the local
14448
%feature("docstring") itk::simple::HMinimaImageFilter::ToString "
14450
Print ourselves out
14454
%feature("docstring") itk::simple::HMinimaImageFilter::~HMinimaImageFilter "
14461
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter "
14463
Base class for specialized complex-to-real inverse Fast Fourier Transform .
14466
This is a base class for the \"inverse\" or \"reverse\" Discrete
14467
Fourier Transform . This is an abstract base class: the actual implementation is
14468
provided by the best child class available on the system when the
14469
object is created via the object factory system.
14471
The input to this filter is assumed to have the same format as the
14472
output of the RealToHalfHermitianForwardFFTImageFilter . That is, the input is assumed to consist of roughly half the full
14473
complex image resulting from a real-to-complex discrete Fourier
14474
transform. This half is expected to be the first half of the image in
14475
the X-dimension. Because this filter assumes that the input stores
14476
only about half of the non-redundant complex pixels, the output is
14477
larger in the X-dimension than it is in the input. To determine the
14478
actual size of the output image, this filter needs additional
14479
information in the form of a flag indicating whether the output image
14480
has an odd size in the X-dimension. Use SetActualXDimensionIsOdd() to set this flag.
14484
ForwardFFTImageFilter , HalfHermitianToRealInverseFFTImageFilter
14486
itk::simple::HalfHermitianToRealInverseFFT for the procedural interface
14488
itk::HalfHermitianToRealInverseFFTImageFilter for the Doxygen on the original ITK class.
14491
C++ includes: sitkHalfHermitianToRealInverseFFTImageFilter.h
14494
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::ActualXDimensionIsOddOff "
14497
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::ActualXDimensionIsOddOn "
14499
Set the value of ActualXDimensionIsOdd to true or false respectfully.
14503
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::Execute "
14505
Execute the filter on the input image
14509
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::Execute "
14511
Execute the filter on the input image with the given parameters
14515
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::GetActualXDimensionIsOdd "
14517
Was the original truncated dimension size odd?
14521
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::GetName "
14527
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::HalfHermitianToRealInverseFFTImageFilter "
14529
Default Constructor that takes no arguments and initializes default
14534
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::SetActualXDimensionIsOdd "
14536
Was the original truncated dimension size odd?
14540
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::ToString "
14542
Print ourselves out
14546
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFTImageFilter::~HalfHermitianToRealInverseFFTImageFilter "
14553
%feature("docstring") itk::simple::HashImageFilter "
14555
Compute the sha1 or md5 hash of an image.
14560
itk::simple::Hash for the procedural interface
14563
C++ includes: sitkHashImageFilter.h
14566
%feature("docstring") itk::simple::HashImageFilter::Execute "
14569
%feature("docstring") itk::simple::HashImageFilter::GetHashFunction "
14572
%feature("docstring") itk::simple::HashImageFilter::GetName "
14578
%feature("docstring") itk::simple::HashImageFilter::HashImageFilter "
14581
%feature("docstring") itk::simple::HashImageFilter::SetHashFunction "
14584
%feature("docstring") itk::simple::HashImageFilter::ToString "
14588
%feature("docstring") itk::simple::HausdorffDistanceImageFilter "
14590
Computes the Hausdorff distance between the set of non-zero pixels of
14594
HausdorffDistanceImageFilter computes the distance between the set non-zero pixels of two images
14595
using the following formula: \\\\[ H(A,B) = \\\\max(h(A,B),h(B,A)) \\\\] where \\\\[ h(A,B) = \\\\max_{a \\\\in A} \\\\min_{b \\\\in B} \\\\| a -
14596
b\\\\| \\\\] is the directed Hausdorff distance and $A$ and $B$ are respectively the set of non-zero pixels in the first and second
14599
In particular, this filter uses the DirectedHausdorffImageFilter
14600
inside to compute the two directed distances and then select the
14601
largest of the two.
14603
The Hausdorff distance measures the degree of mismatch between two
14604
sets and behaves like a metric over the set of all closed bounded sets
14605
- with properties of identity, symmetry and triangle inequality.
14607
This filter requires the largest possible region of the first image
14608
and the same corresponding region in the second image. It behaves as
14609
filter with two inputs and one output. Thus it can be inserted in a
14610
pipeline with other filters. The filter passes the first input through
14613
This filter is templated over the two input image types. It assume
14614
both images have the same number of dimensions.
14618
DirectedHausdorffDistanceImageFilter
14620
itk::HausdorffDistanceImageFilter for the Doxygen on the original ITK class.
14623
C++ includes: sitkHausdorffDistanceImageFilter.h
14626
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::Execute "
14628
Execute the filter on the input images
14632
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::GetAverageHausdorffDistance "
14634
Return the computed Hausdorff distance.
14636
This is a measurement. Its value is updated in the Execute methods, so
14637
the value will only be valid after an execution.
14641
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::GetHausdorffDistance "
14643
Return the computed Hausdorff distance.
14645
This is a measurement. Its value is updated in the Execute methods, so
14646
the value will only be valid after an execution.
14650
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::GetName "
14656
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::HausdorffDistanceImageFilter "
14658
Default Constructor that takes no arguments and initializes default
14663
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::ToString "
14665
Print ourselves out
14669
%feature("docstring") itk::simple::HausdorffDistanceImageFilter::~HausdorffDistanceImageFilter "
14676
%feature("docstring") itk::simple::HistogramMatchingImageFilter "
14678
Normalize the grayscale values between two images by histogram
14682
HistogramMatchingImageFilter normalizes the grayscale values of a source image based on the
14683
grayscale values of a reference image. This filter uses a histogram
14684
matching technique where the histograms of the two images are matched
14685
only at a specified number of quantile values.
14687
This filter was originally designed to normalize MR images of the same
14688
MR protocol and same body part. The algorithm works best if background
14689
pixels are excluded from both the source and reference histograms. A
14690
simple background exclusion method is to exclude all pixels whose
14691
grayscale values are smaller than the mean grayscale value. ThresholdAtMeanIntensityOn() switches on this simple background exclusion method.
14693
The source image can be set via either SetInput() or SetSourceImage()
14694
. The reference image can be set via SetReferenceImage() .
14696
SetNumberOfHistogramLevels() sets the number of bins used when creating histograms of the source
14697
and reference images. SetNumberOfMatchPoints() governs the number of quantile values to be matched.
14699
This filter assumes that both the source and reference are of the same
14700
type and that the input and output image type have the same number of
14701
dimension and have scalar pixel types.
14704
Laszlo G. Nyul, Jayaram K. Udupa, and Xuan Zhang, \"New Variants of a
14705
Method of MRI Scale Standardization\", IEEE Transactions on Medical
14706
Imaging, 19(2):143-150, 2000.
14709
itk::simple::HistogramMatching for the procedural interface
14711
itk::HistogramMatchingImageFilter for the Doxygen on the original ITK class.
14714
C++ includes: sitkHistogramMatchingImageFilter.h
14717
%feature("docstring") itk::simple::HistogramMatchingImageFilter::Execute "
14719
Execute the filter on the input images
14723
%feature("docstring") itk::simple::HistogramMatchingImageFilter::Execute "
14725
Execute the filter on the input images with the given parameters
14729
%feature("docstring") itk::simple::HistogramMatchingImageFilter::GetName "
14735
%feature("docstring") itk::simple::HistogramMatchingImageFilter::GetNumberOfHistogramLevels "
14737
Set/Get the number of histogram levels used.
14741
%feature("docstring") itk::simple::HistogramMatchingImageFilter::GetNumberOfMatchPoints "
14743
Set/Get the number of match points used.
14747
%feature("docstring") itk::simple::HistogramMatchingImageFilter::GetThresholdAtMeanIntensity "
14749
Set/Get the threshold at mean intensity flag. If true, only source
14750
(reference) pixels which are greater than the mean source (reference)
14751
intensity is used in the histogram matching. If false, all pixels are
14756
%feature("docstring") itk::simple::HistogramMatchingImageFilter::HistogramMatchingImageFilter "
14758
Default Constructor that takes no arguments and initializes default
14763
%feature("docstring") itk::simple::HistogramMatchingImageFilter::SetNumberOfHistogramLevels "
14765
Set/Get the number of histogram levels used.
14769
%feature("docstring") itk::simple::HistogramMatchingImageFilter::SetNumberOfMatchPoints "
14771
Set/Get the number of match points used.
14775
%feature("docstring") itk::simple::HistogramMatchingImageFilter::SetThresholdAtMeanIntensity "
14777
Set/Get the threshold at mean intensity flag. If true, only source
14778
(reference) pixels which are greater than the mean source (reference)
14779
intensity is used in the histogram matching. If false, all pixels are
14784
%feature("docstring") itk::simple::HistogramMatchingImageFilter::ThresholdAtMeanIntensityOff "
14787
%feature("docstring") itk::simple::HistogramMatchingImageFilter::ThresholdAtMeanIntensityOn "
14789
Set the value of ThresholdAtMeanIntensity to true or false
14794
%feature("docstring") itk::simple::HistogramMatchingImageFilter::ToString "
14796
Print ourselves out
14800
%feature("docstring") itk::simple::HistogramMatchingImageFilter::~HistogramMatchingImageFilter "
14807
%feature("docstring") itk::simple::HuangThresholdImageFilter "
14809
Threshold an image using the Huang Threshold.
14812
This filter creates a binary thresholded image that separates an image
14813
into foreground and background components. The filter computes the
14814
threshold using the HuangThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
14817
Richard Beare. Department of Medicine, Monash University, Melbourne,
14819
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
14820
de Jouy-en-Josas, France.
14822
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
14826
HistogramThresholdImageFilter
14828
itk::simple::HuangThreshold for the procedural interface
14830
itk::HuangThresholdImageFilter for the Doxygen on the original ITK class.
14833
C++ includes: sitkHuangThresholdImageFilter.h
14836
%feature("docstring") itk::simple::HuangThresholdImageFilter::Execute "
14838
Execute the filter on the input image
14842
%feature("docstring") itk::simple::HuangThresholdImageFilter::Execute "
14845
%feature("docstring") itk::simple::HuangThresholdImageFilter::Execute "
14847
Execute the filter on the input image with the given parameters
14851
%feature("docstring") itk::simple::HuangThresholdImageFilter::Execute "
14854
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetInsideValue "
14856
Get the \"inside\" pixel value.
14860
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetMaskOutput "
14863
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetMaskValue "
14866
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetName "
14872
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetNumberOfHistogramBins "
14875
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetOutsideValue "
14877
Get the \"outside\" pixel value.
14881
%feature("docstring") itk::simple::HuangThresholdImageFilter::GetThreshold "
14883
Get the computed threshold.
14886
This is a measurement. Its value is updated in the Execute methods, so
14887
the value will only be valid after an execution.
14891
%feature("docstring") itk::simple::HuangThresholdImageFilter::HuangThresholdImageFilter "
14893
Default Constructor that takes no arguments and initializes default
14898
%feature("docstring") itk::simple::HuangThresholdImageFilter::MaskOutputOff "
14901
%feature("docstring") itk::simple::HuangThresholdImageFilter::MaskOutputOn "
14903
Set the value of MaskOutput to true or false respectfully.
14907
%feature("docstring") itk::simple::HuangThresholdImageFilter::SetInsideValue "
14909
Set the \"inside\" pixel value. The default value NumericTraits<OutputPixelType>::max()
14913
%feature("docstring") itk::simple::HuangThresholdImageFilter::SetMaskOutput "
14915
Do you want the output to be masked by the mask used in histogram
14916
construction. Only relevant if masking is in use.
14920
%feature("docstring") itk::simple::HuangThresholdImageFilter::SetMaskValue "
14922
The value in the mask image, if used, indicating voxels that should be
14923
included. Default is the max of pixel type, as in the
14924
MaskedImageToHistogramFilter
14928
%feature("docstring") itk::simple::HuangThresholdImageFilter::SetNumberOfHistogramBins "
14930
Set/Get the number of histogram bins. Defaults is 128.
14934
%feature("docstring") itk::simple::HuangThresholdImageFilter::SetOutsideValue "
14936
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
14940
%feature("docstring") itk::simple::HuangThresholdImageFilter::ToString "
14942
Print ourselves out
14946
%feature("docstring") itk::simple::HuangThresholdImageFilter::~HuangThresholdImageFilter "
14953
%feature("docstring") itk::simple::Image "
14955
The main Image class for SimpleITK.
14957
C++ includes: sitkImage.h
14960
%feature("docstring") itk::simple::Image::CopyInformation "
14962
Copy common meta-data from an image to this one.
14965
Copies the Origin, Spacing, and Direction from the source image to
14966
this image. The meta-data dictionary is not copied.
14968
It is required for the source Image's dimension and size to match, this image's attributes, otherwise an
14969
exception will be generated.
14973
%feature("docstring") itk::simple::Image::EraseMetaData "
14975
Remove an entry from the meta-data dictionary.
14978
Returns true, when the value exists in the dictionary and is removed,
14983
%feature("docstring") itk::simple::Image::GetDepth "
14986
%feature("docstring") itk::simple::Image::GetDimension "
14989
%feature("docstring") itk::simple::Image::GetHeight "
14992
%feature("docstring") itk::simple::Image::GetMetaData "
14994
Get the value of a meta-data dictionary entry as a string.
14997
If the key is not in the dictionary then an exception is thrown.
14999
string types in the dictionary are returned as their native strings.
15000
Other types are printed to string before returning.
15004
%feature("docstring") itk::simple::Image::GetMetaDataKeys "
15006
get a vector of keys in from the meta-data dictionary
15009
Returns a vector of keys to the key/value entries in the image's meta-
15010
data dictionary. Iterate through with these keys to get the values.
15014
%feature("docstring") itk::simple::Image::GetNumberOfComponentsPerPixel "
15016
Get the number of components for each pixel.
15019
For scalar images this methods returns 1. For vector images the number
15020
of components for each pixel is returned.
15024
%feature("docstring") itk::simple::Image::GetNumberOfPixels "
15026
Get the number of pixels in the image.
15029
To Calculate the total number of values stored continuously for the
15030
image's buffer, the NumberOfPixels should be multiplied by
15031
NumberOfComponentsPerPixel in order to account for multiple component
15036
%feature("docstring") itk::simple::Image::GetPixelID "
15039
%feature("docstring") itk::simple::Image::GetPixelIDTypeAsString "
15042
%feature("docstring") itk::simple::Image::GetPixelIDValue "
15045
%feature("docstring") itk::simple::Image::GetSize "
15048
%feature("docstring") itk::simple::Image::GetWidth "
15051
%feature("docstring") itk::simple::Image::HasMetaDataKey "
15053
Query the meta-data dictionary for the existence of a key.
15057
%feature("docstring") itk::simple::Image::Image "
15059
Default constructor, creates an image of size 0.
15063
%feature("docstring") itk::simple::Image::Image "
15066
%feature("docstring") itk::simple::Image::MakeUnique "
15068
Performs actually coping if needed to make object unique.
15071
The Image class by default performs lazy coping and assignment. This method
15072
make sure that coping actually happens to the itk::Image pointed to is only pointed to by this object.
15076
%feature("docstring") itk::simple::Image::SetMetaData "
15078
Set an entry in the meta-data dictionary.
15081
Replaces or creates an entry in the image's meta-data dictionary.
15085
%feature("docstring") itk::simple::Image::ToString "
15088
%feature("docstring") itk::simple::Image::TransformContinuousIndexToPhysicalPoint "
15090
Transform continuous index to physical point
15094
%feature("docstring") itk::simple::Image::TransformIndexToPhysicalPoint "
15096
Transform index to physical point
15100
%feature("docstring") itk::simple::Image::TransformPhysicalPointToContinuousIndex "
15102
Transform physical point to continuous index
15106
%feature("docstring") itk::simple::Image::TransformPhysicalPointToIndex "
15108
Transform physical point to index
15112
%feature("docstring") itk::simple::Image::~Image "
15116
%feature("docstring") itk::simple::ImageFileReader "
15118
Read a 2D or 3D image and return a smart pointer to a SimpleITK image.
15121
This reader handles scalar and vector images and returns an image with
15122
the same type as the file on disk.
15126
itk::simple::ReadImage for the procedural interface
15129
C++ includes: sitkImageFileReader.h
15132
%feature("docstring") itk::simple::ImageFileReader::Execute "
15135
%feature("docstring") itk::simple::ImageFileReader::GetFileName "
15138
%feature("docstring") itk::simple::ImageFileReader::GetName "
15140
return user readable name fo the filter
15144
%feature("docstring") itk::simple::ImageFileReader::ImageFileReader "
15147
%feature("docstring") itk::simple::ImageFileReader::SetFileName "
15150
%feature("docstring") itk::simple::ImageFileReader::ToString "
15152
Print ourselves to string
15157
%feature("docstring") itk::simple::ImageFileWriter "
15159
Write out a SimpleITK image to the specified file location.
15162
This writer tries to write the image out using the image's type to the
15163
location specified in FileName. If writing fails, an ITK exception is
15168
itk::simple::WriteImage for the procedural interface
15171
C++ includes: sitkImageFileWriter.h
15174
%feature("docstring") itk::simple::ImageFileWriter::Execute "
15177
%feature("docstring") itk::simple::ImageFileWriter::Execute "
15180
%feature("docstring") itk::simple::ImageFileWriter::GetFileName "
15183
%feature("docstring") itk::simple::ImageFileWriter::GetName "
15185
return user readable name fo the filter
15189
%feature("docstring") itk::simple::ImageFileWriter::ImageFileWriter "
15192
%feature("docstring") itk::simple::ImageFileWriter::SetFileName "
15195
%feature("docstring") itk::simple::ImageFileWriter::ToString "
15197
Print ourselves to string
15202
%feature("docstring") itk::simple::ImageFilter "
15204
The base interface for SimpleITK filters that take one input image.
15207
All SimpleITK filters which take one input image should inherit from
15210
C++ includes: sitkImageFilter.h
15213
%feature("docstring") itk::simple::ImageFilter::ImageFilter "
15215
Default Constructor that takes no arguments and initializes default
15220
%feature("docstring") itk::simple::ImageFilter::~ImageFilter "
15227
%feature("docstring") itk::simple::ImageReaderBase "
15229
An abract base class for image readers.
15231
C++ includes: sitkImageReaderBase.h
15234
%feature("docstring") itk::simple::ImageReaderBase::Execute "
15237
%feature("docstring") itk::simple::ImageReaderBase::ImageReaderBase "
15240
%feature("docstring") itk::simple::ImageReaderBase::ToString "
15244
%feature("docstring") itk::simple::ImageRegistrationMethod "
15246
An interface method to the modular ITKv4 registration framework.
15249
This interface method class encapsulates typical registration usage by
15250
incorporating all the necessary elements for performing a simple image
15251
registration between two images. This method also allows for
15252
multistage registration whereby each stage is characterized by
15253
possibly different transforms and different image metrics. For
15254
example, many users will want to perform a linear registration
15255
followed by deformable registration where both stages are performed in
15256
multiple levels. Each level can be characterized by:
15259
the resolution of the virtual domain image (see below)
15261
smoothing of the fixed and moving images
15262
Multiple stages are handled by linking multiple instantiations of
15263
this class where the output transform is added to the optional
15264
composite transform input.
15268
itk::ImageRegistrationMethodv4
15270
itk::ImageToImageMetricv4
15272
itk::ObjectToObjectOptimizerBaseTemplate
15275
C++ includes: sitkImageRegistrationMethod.h
15278
%feature("docstring") itk::simple::ImageRegistrationMethod::Execute "
15280
Optimize the configured registration problem.
15284
%feature("docstring") itk::simple::ImageRegistrationMethod::GetCurrentLevel "
15287
%feature("docstring") itk::simple::ImageRegistrationMethod::GetMetricValue "
15290
%feature("docstring") itk::simple::ImageRegistrationMethod::GetName "
15292
return user readable name for the filter
15296
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerConvergenceValue "
15299
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerIteration "
15301
Active measurements which can be obtained during call backs.
15303
This is a measurement. Its value is updated in the Execute methods, so
15304
the value will only be valid after an execution.
15308
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerLearningRate "
15311
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerPosition "
15314
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerScales "
15316
Get the OptimizerScales.
15319
If the scales are explicitly set then this method returns those
15320
values. If an estimator is used then this is an active measurement
15321
returning the scales estimated by the estimator and is only available
15326
%feature("docstring") itk::simple::ImageRegistrationMethod::GetOptimizerStopConditionDescription "
15328
Measurement updated at the end of execution.
15332
%feature("docstring") itk::simple::ImageRegistrationMethod::ImageRegistrationMethod "
15335
%feature("docstring") itk::simple::ImageRegistrationMethod::MetricEvaluate "
15337
Get the value of the metric given the state of the method.
15340
Passing a fixed and moving image, this method constructs and
15341
configures a metric object to obtain the value. This will take into
15342
consideration the current transforms, metric, interpolator, and image
15343
masks. It does not take into consideration the sampling strategy,
15344
smoothing sigmas, or the shrink factors.
15348
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsANTSNeighborhoodCorrelation "
15350
Use normalized cross correlation using a small neighborhood for each
15351
voxel between two images, with speed optimizations for dense
15357
itk::ANTSNeighborhoodCorrelationImageToImageMetricv4
15362
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsCorrelation "
15364
Use negative normalized cross correlation image metric.
15369
itk::CorrelationImageToImageMetricv4
15374
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsDemons "
15376
Use demons image metric.
15381
itk::DemonsImageToImageMetricv4
15386
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsJointHistogramMutualInformation "
15388
Use mutual information between two images.
15393
itk::JointHistogramMutualInformationImageToImageMetricv4
15398
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsMattesMutualInformation "
15400
Use the mutual information between two images to be registered using
15401
the method of Mattes et al.
15406
itk::MattesMutualInformationImageToImageMetricv4
15411
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricAsMeanSquares "
15413
Use negative means squares image metric.
15418
itk::MeanSquaresImageToImageMetricv4
15423
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricFixedMask "
15425
Set an image mask in order to restrict the sampled points for the
15429
The image is expected to be in the same physical space as the
15430
FixedImage, and if the pixel type is not UInt8 than the image will
15435
itk::ImageToImageMetricv4::SetFixedImageMask
15440
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricMovingMask "
15442
Set an image mask in order to restrict the sampled points for the
15443
metric in the moving image space.
15446
The image is expected to be in the same physical space as the
15447
MovingImage, and if the pixel type is not UInt8 than the image will
15452
itk::ImageToImageMetricv4::SetMovingImageMask
15457
%feature("docstring") itk::simple::ImageRegistrationMethod::SetMetricSamplingStrategy "
15459
Set sampling strategy for sample generation.
15464
itk::ImageRegistrationMethodv4::SetMetricSamplingStrategy
15469
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsAmoeba "
15471
Set optimizer to Nelder-Mead downhill simplex algorithm.
15476
itk::AmoebaOptimizerv4
15481
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsConjugateGradientLineSearch "
15483
Conjugate gradient descent optimizer with a golden section line search
15484
for nonlinear optimization.
15489
itk::ConjugateGradientLineSearchOptimizerv4Template
15494
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsExhaustive "
15496
Set the optimizer to sample the metric at regular steps.
15499
At each iteration the GetOptimizerIteration, can be used to index into
15500
the sampling grid along with the GetCurrentMetricValue.
15502
The resulting transform and value at the end of execution is the best
15505
The OptimizerScales can be used to perform anisotropic sampling.
15508
This optimizer is not suitable for use in conjunction with the
15512
itk::ExhaustiveOptimizerv4
15517
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsGradientDescent "
15519
Gradient descent optimizer.
15524
itk::GradientDescentOptimizerv4Template
15529
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsGradientDescentLineSearch "
15531
Gradient descent optimizer with a golden section line search.
15536
itk::GradientDescentLineSearchOptimizerv4Template
15541
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsLBFGSB "
15543
Limited memory Broyden Fletcher Goldfarb Shannon minimization with
15547
The default parameters utilize LBFGSB in unbounded mode.
15551
itk::LBFGSBOptimizerv4
15556
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsOnePlusOneEvolutionary "
15558
1+1 evolutionary optimizer strategy.
15561
The seed parameter is used to seed the pseudo-random number generator.
15562
If the seed parameter is 0, then the wall clock is used to seed,
15563
otherwise the fixed seed is used for reproducible behavior.
15567
itk::OnePlusOneEvolutionaryOptimizerv4
15572
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsPowell "
15574
Powell optimization using Brent line search.
15579
itk::PowellOptimizerv4
15584
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerAsRegularStepGradientDescent "
15586
Regular Step Gradient descent optimizer.
15591
itk::RegularStepGradientDescentOptimizerv4
15596
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerScales "
15598
Manually set per parameter weighting for the transform parameters.
15602
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerScalesFromIndexShift "
15604
Estimate scales from maximum voxel shift in index space cause by
15610
itk::RegistrationParameterScalesFromIndexShift
15615
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerScalesFromJacobian "
15617
Estimate scales from Jacobian norms.
15620
This scales estimator works well with versor based transforms.
15624
itk::RegistrationParameterScalesFromJacobian
15629
%feature("docstring") itk::simple::ImageRegistrationMethod::SetOptimizerScalesFromPhysicalShift "
15631
Estimating scales of transform parameters a step sizes, from the
15632
maximum voxel shift in physical space caused by a parameter change.
15637
itk::RegistrationParameterScalesFromPhysicalShift
15642
%feature("docstring") itk::simple::ImageRegistrationMethod::SetShrinkFactorsPerLevel "
15644
Set the shrink factors for each level where each level has the same
15645
shrink factor for each dimension.
15650
itk::ImageRegistrationMethodv4::SetShrinkFactorsPerLevel
15655
%feature("docstring") itk::simple::ImageRegistrationMethod::SetSmoothingSigmasPerLevel "
15657
Set the sigmas of Gaussian used for smoothing at each level.
15662
itk::ImageRegistrationMethodv4::SetSmoothingSigmasPerLevel
15667
%feature("docstring") itk::simple::ImageRegistrationMethod::ToString "
15669
Print the information about the object to a string.
15672
If called when the process is being executed ( during a callback ),
15673
the ITK Optimizer and Transform objects will be printed.
15677
%feature("docstring") itk::simple::ImageRegistrationMethod::~ImageRegistrationMethod "
15681
%feature("docstring") itk::simple::ImageSeriesReader "
15683
Read series of image into a SimpleITK image.
15688
itk::simple::ReadImage for the procedural interface
15691
C++ includes: sitkImageSeriesReader.h
15694
%feature("docstring") itk::simple::ImageSeriesReader::Execute "
15697
%feature("docstring") itk::simple::ImageSeriesReader::GetFileNames "
15700
%feature("docstring") itk::simple::ImageSeriesReader::GetName "
15702
return user readable name fo the filter
15706
%feature("docstring") itk::simple::ImageSeriesReader::ImageSeriesReader "
15709
%feature("docstring") itk::simple::ImageSeriesReader::SetFileNames "
15712
%feature("docstring") itk::simple::ImageSeriesReader::ToString "
15714
Print ourselves to string
15719
%feature("docstring") itk::simple::ImageSeriesWriter "
15721
Writer series of image from a SimpleITK image.
15724
The ImageSeriesWriter is for writing a 3D image as a series of 2D images. A list of names
15725
for the series of 2D images must be provided, and an exception will be
15726
generated if the number of file names does not match the size of the
15727
image in the z-direction.
15729
DICOM series cannot be written with this class, as an exception will
15730
be generated. To write a DICOM series the individual slices must be
15731
extracted, proper DICOM tags must be added to the dictionaries, then
15732
written with the ImageFileWriter.
15736
itk::simple::WriteImage for the procedural interface
15739
C++ includes: sitkImageSeriesWriter.h
15742
%feature("docstring") itk::simple::ImageSeriesWriter::Execute "
15745
%feature("docstring") itk::simple::ImageSeriesWriter::Execute "
15748
%feature("docstring") itk::simple::ImageSeriesWriter::GetName "
15750
return user readable name fo the filter
15754
%feature("docstring") itk::simple::ImageSeriesWriter::ImageSeriesWriter "
15757
%feature("docstring") itk::simple::ImageSeriesWriter::ToString "
15759
Print ourselves to string
15764
%feature("docstring") itk::simple::ImportImageFilter "
15766
Compose a 2D or 3D image and return a smart pointer to a SimpleITK
15770
This filter is intended to interface SimpleITK to other image
15771
processing libraries and applications that may have their own
15772
representation of an image class. It creates a SimpleITK image which
15773
shares the bulk data buffer as what is set. SimpleITK will not
15774
responsible to delete the buffer afterwards, and it buffer must remain
15775
valid while in use.
15779
itk::simple::ImportAsInt8, itk::simple::ImportAsUInt8, itk::simple::ImportAsInt16, itk::simple::ImportAsUInt16, itk::simple::ImportAsInt32, itk::simple::ImportAsUInt32, itk::simple::ImportAsInt64, itk::simple::ImportAsUInt64, itk::simple::ImportAsFloat, itk::simple::ImportAsDouble for the procedural interfaces.
15782
C++ includes: sitkImportImageFilter.h
15785
%feature("docstring") itk::simple::ImportImageFilter::Execute "
15788
%feature("docstring") itk::simple::ImportImageFilter::GetDirection "
15791
%feature("docstring") itk::simple::ImportImageFilter::GetName "
15793
return user readable name fo the filter
15797
%feature("docstring") itk::simple::ImportImageFilter::GetOrigin "
15800
%feature("docstring") itk::simple::ImportImageFilter::GetSize "
15803
%feature("docstring") itk::simple::ImportImageFilter::GetSpacing "
15806
%feature("docstring") itk::simple::ImportImageFilter::ImportImageFilter "
15809
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsDouble "
15812
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsFloat "
15815
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsInt16 "
15818
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsInt32 "
15821
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsInt64 "
15824
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsInt8 "
15827
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsUInt16 "
15830
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsUInt32 "
15833
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsUInt64 "
15836
%feature("docstring") itk::simple::ImportImageFilter::SetBufferAsUInt8 "
15839
%feature("docstring") itk::simple::ImportImageFilter::SetDirection "
15842
%feature("docstring") itk::simple::ImportImageFilter::SetOrigin "
15845
%feature("docstring") itk::simple::ImportImageFilter::SetSize "
15848
%feature("docstring") itk::simple::ImportImageFilter::SetSpacing "
15851
%feature("docstring") itk::simple::ImportImageFilter::ToString "
15853
Print ourselves to string
15858
%feature("docstring") itk::simple::IntensityWindowingImageFilter "
15860
Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval
15861
are mapped to a constant. Values over the interval are mapped to
15865
IntensityWindowingImageFilter applies pixel-wise a linear transformation to the intensity values of
15866
input image pixels. The linear transformation is defined by the user
15867
in terms of the minimum and maximum values that the output image
15868
should have and the lower and upper limits of the intensity window of
15869
the input image. This operation is very common in visualization, and
15870
can also be applied as a convenient preprocessing operation for image
15873
All computations are performed in the precision of the input pixel's
15874
RealType. Before assigning the computed value to the output pixel.
15880
IntensityWindowingImageFilter
15883
RescaleIntensityImageFilter
15885
itk::simple::IntensityWindowing for the procedural interface
15887
itk::IntensityWindowingImageFilter for the Doxygen on the original ITK class.
15890
C++ includes: sitkIntensityWindowingImageFilter.h
15893
%feature("docstring") itk::simple::IntensityWindowingImageFilter::Execute "
15895
Execute the filter on the input image
15899
%feature("docstring") itk::simple::IntensityWindowingImageFilter::Execute "
15901
Execute the filter on the input image with the given parameters
15905
%feature("docstring") itk::simple::IntensityWindowingImageFilter::GetName "
15911
%feature("docstring") itk::simple::IntensityWindowingImageFilter::GetOutputMaximum "
15913
Set/Get the values of the maximum and minimum intensities of the
15918
%feature("docstring") itk::simple::IntensityWindowingImageFilter::GetOutputMinimum "
15920
Set/Get the values of the maximum and minimum intensities of the
15925
%feature("docstring") itk::simple::IntensityWindowingImageFilter::GetWindowMaximum "
15927
Set/Get the values of the maximum and minimum intensities of the input
15932
%feature("docstring") itk::simple::IntensityWindowingImageFilter::GetWindowMinimum "
15934
Set/Get the values of the maximum and minimum intensities of the input
15939
%feature("docstring") itk::simple::IntensityWindowingImageFilter::IntensityWindowingImageFilter "
15941
Default Constructor that takes no arguments and initializes default
15946
%feature("docstring") itk::simple::IntensityWindowingImageFilter::SetOutputMaximum "
15948
Set/Get the values of the maximum and minimum intensities of the
15953
%feature("docstring") itk::simple::IntensityWindowingImageFilter::SetOutputMinimum "
15955
Set/Get the values of the maximum and minimum intensities of the
15960
%feature("docstring") itk::simple::IntensityWindowingImageFilter::SetWindowMaximum "
15962
Set/Get the values of the maximum and minimum intensities of the input
15967
%feature("docstring") itk::simple::IntensityWindowingImageFilter::SetWindowMinimum "
15969
Set/Get the values of the maximum and minimum intensities of the input
15974
%feature("docstring") itk::simple::IntensityWindowingImageFilter::ToString "
15976
Print ourselves out
15980
%feature("docstring") itk::simple::IntensityWindowingImageFilter::~IntensityWindowingImageFilter "
15987
%feature("docstring") itk::simple::IntermodesThresholdImageFilter "
15989
Threshold an image using the Intermodes Threshold.
15992
This filter creates a binary thresholded image that separates an image
15993
into foreground and background components. The filter computes the
15994
threshold using the IntermodesThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
15997
Richard Beare. Department of Medicine, Monash University, Melbourne,
15999
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
16000
de Jouy-en-Josas, France.
16002
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
16006
HistogramThresholdImageFilter
16008
itk::simple::IntermodesThreshold for the procedural interface
16010
itk::IntermodesThresholdImageFilter for the Doxygen on the original ITK class.
16013
C++ includes: sitkIntermodesThresholdImageFilter.h
16016
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::Execute "
16018
Execute the filter on the input image
16022
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::Execute "
16025
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::Execute "
16027
Execute the filter on the input image with the given parameters
16031
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::Execute "
16034
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetInsideValue "
16036
Get the \"inside\" pixel value.
16040
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetMaskOutput "
16043
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetMaskValue "
16046
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetName "
16052
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetNumberOfHistogramBins "
16055
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetOutsideValue "
16057
Get the \"outside\" pixel value.
16061
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::GetThreshold "
16063
Get the computed threshold.
16066
This is a measurement. Its value is updated in the Execute methods, so
16067
the value will only be valid after an execution.
16071
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::IntermodesThresholdImageFilter "
16073
Default Constructor that takes no arguments and initializes default
16078
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::MaskOutputOff "
16081
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::MaskOutputOn "
16083
Set the value of MaskOutput to true or false respectfully.
16087
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::SetInsideValue "
16089
Set the \"inside\" pixel value.
16093
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::SetMaskOutput "
16095
Do you want the output to be masked by the mask used in histogram
16096
construction. Only relevant if masking is in use.
16100
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::SetMaskValue "
16102
The value in the mask image, if used, indicating voxels that should be
16103
included. Default is the max of pixel type, as in the
16104
MaskedImageToHistogramFilter
16108
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::SetNumberOfHistogramBins "
16110
Set/Get the number of histogram bins.
16114
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::SetOutsideValue "
16116
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
16120
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::ToString "
16122
Print ourselves out
16126
%feature("docstring") itk::simple::IntermodesThresholdImageFilter::~IntermodesThresholdImageFilter "
16133
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter "
16135
The direct linear inverse deconvolution filter.
16138
The inverse filter is the most straightforward deconvolution method.
16139
Considering that convolution of two images in the spatial domain is
16140
equivalent to multiplying the Fourier transform of the two images, the
16141
inverse filter consists of inverting the multiplication. In other
16142
words, this filter computes the following: \\\\[ hat{F}(\\\\omega) = \\\\begin{cases} G(\\\\omega) / H(\\\\omega)
16143
& \\\\text{if \\\\f$|H(\\\\omega)| \\\\geq \\\\epsilon\\\\f$} \\\\\\\\
16144
0 & \\\\text{otherwise} \\\\end{cases} \\\\] where $\\\\hat{F}(\\\\omega)$ is the Fourier transform of the estimate produced by this filter, $G(\\\\omega)$ is the Fourier transform of the input blurred image, $H(\\\\omega)$ is the Fourier transform of the blurring kernel, and $\\\\epsilon$ is a constant real non-negative threshold (called
16145
KernelZeroMagnitudeThreshold in this filter) that determines when the
16146
magnitude of a complex number is considered zero.
16149
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
16150
de Jouy-en-Josas, France
16151
Cory Quammen, The University of North Carolina at Chapel Hill
16153
itk::simple::InverseDeconvolution for the procedural interface
16155
itk::InverseDeconvolutionImageFilter for the Doxygen on the original ITK class.
16158
C++ includes: sitkInverseDeconvolutionImageFilter.h
16161
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::Execute "
16163
Execute the filter on the input images
16167
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::Execute "
16169
Execute the filter on the input images with the given parameters
16173
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::GetBoundaryCondition "
16176
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::GetKernelZeroMagnitudeThreshold "
16178
Set/get the threshold value uused to determine whether a frequency of
16179
the Fourier transform of the blurring kernel is considered to be zero.
16180
Default value is 1.0e-4.
16184
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::GetName "
16190
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::GetNormalize "
16193
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::GetOutputRegionMode "
16196
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::InverseDeconvolutionImageFilter "
16198
Default Constructor that takes no arguments and initializes default
16203
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::NormalizeOff "
16206
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::NormalizeOn "
16208
Set the value of Normalize to true or false respectfully.
16212
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::SetBoundaryCondition "
16215
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::SetKernelZeroMagnitudeThreshold "
16217
Set/get the threshold value uused to determine whether a frequency of
16218
the Fourier transform of the blurring kernel is considered to be zero.
16219
Default value is 1.0e-4.
16223
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::SetNormalize "
16225
Normalize the output image by the sum of the kernel components
16229
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::SetOutputRegionMode "
16232
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::ToString "
16234
Print ourselves out
16238
%feature("docstring") itk::simple::InverseDeconvolutionImageFilter::~InverseDeconvolutionImageFilter "
16245
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter "
16247
Computes the inverse of a displacement field.
16250
InverseDisplacementFieldImageFilter takes a displacement field as input and computes the displacement
16251
field that is its inverse. If the input displacement field was mapping
16252
coordinates from a space A into a space B, the output of this filter
16253
will map coordinates from the space B into the space A.
16255
Given that both the input and output displacement field are
16256
represented as discrete images with pixel type vector, the inverse
16257
will be only an estimation and will probably not correspond to a
16258
perfect inverse. The precision of the inverse can be improved at the
16259
price of increasing the computation time and memory consumption in
16262
The method used for computing the inverse displacement field is to
16263
subsample the input field using a regular grid and create Kerned-Base
16264
Spline in which the reference landmarks are the coordinates of the
16265
deformed point and the target landmarks are the negative of the
16266
displacement vectors. The kernel-base spline is then used for
16267
regularly sampling the output space and recover vector values for
16268
every single pixel.
16270
The subsampling factor used for the regular grid of the input field
16271
will determine the number of landmarks in the KernelBased spline and
16272
therefore it will have a dramatic effect on both the precision of
16273
output displacement field and the computational time required for the
16274
filter to complete the estimation. A large subsampling factor will
16275
result in few landmarks in the KernelBased spline, therefore on fast
16276
computation and low precision. A small subsampling factor will result
16277
in a large number of landmarks in the KernelBased spline, therefore a
16278
large memory consumption, long computation time and high precision for
16279
the inverse estimation.
16281
This filter expects both the input and output images to be of pixel
16284
itk::simple::InverseDisplacementField for the procedural interface
16286
itk::InverseDisplacementFieldImageFilter for the Doxygen on the original ITK class.
16289
C++ includes: sitkInverseDisplacementFieldImageFilter.h
16292
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::Execute "
16294
Execute the filter on the input image
16298
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::Execute "
16300
Execute the filter on the input image with the given parameters
16304
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::GetName "
16310
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::GetOutputOrigin "
16312
Get the output image origin.
16316
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::GetOutputSpacing "
16318
Get the output image spacing.
16322
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::GetSize "
16324
Get the size of the output image.
16328
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::GetSubsamplingFactor "
16330
Set/Get the factor used for subsampling the input displacement field.
16331
A large value in this factor will produce a fast computation of the
16332
inverse field but with low precision. A small value of this factor
16333
will produce a precise computation of the inverse field at the price
16334
of large memory consumption and long computational time.
16338
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::InverseDisplacementFieldImageFilter "
16340
Default Constructor that takes no arguments and initializes default
16345
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::SetOutputOrigin "
16347
Set the output image origin.
16351
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::SetOutputSpacing "
16353
Set the output image spacing.
16357
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::SetReferenceImage "
16359
This methods sets the output size, origin, and direction to that of
16364
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::SetSize "
16366
Set the size of the output image.
16370
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::SetSubsamplingFactor "
16372
Set/Get the factor used for subsampling the input displacement field.
16373
A large value in this factor will produce a fast computation of the
16374
inverse field but with low precision. A small value of this factor
16375
will produce a precise computation of the inverse field at the price
16376
of large memory consumption and long computational time.
16380
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::ToString "
16382
Print ourselves out
16386
%feature("docstring") itk::simple::InverseDisplacementFieldImageFilter::~InverseDisplacementFieldImageFilter "
16393
%feature("docstring") itk::simple::InverseFFTImageFilter "
16395
Base class for inverse Fast Fourier Transform .
16398
This is a base class for the \"inverse\" or \"reverse\" Discrete
16399
Fourier Transform . This is an abstract base class: the actual implementation is
16400
provided by the best child available on the system when the object is
16401
created via the object factory system.
16403
This class transforms a full complex image with Hermitian symmetry
16404
into its real spatial domain representation. If the input does not
16405
have Hermitian symmetry, the imaginary component is discarded.
16409
ForwardFFTImageFilter , InverseFFTImageFilter
16411
itk::simple::InverseFFT for the procedural interface
16413
itk::InverseFFTImageFilter for the Doxygen on the original ITK class.
16416
C++ includes: sitkInverseFFTImageFilter.h
16419
%feature("docstring") itk::simple::InverseFFTImageFilter::Execute "
16421
Execute the filter on the input image
16425
%feature("docstring") itk::simple::InverseFFTImageFilter::GetName "
16431
%feature("docstring") itk::simple::InverseFFTImageFilter::InverseFFTImageFilter "
16433
Default Constructor that takes no arguments and initializes default
16438
%feature("docstring") itk::simple::InverseFFTImageFilter::ToString "
16440
Print ourselves out
16444
%feature("docstring") itk::simple::InverseFFTImageFilter::~InverseFFTImageFilter "
16451
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter "
16453
Iteratively estimate the inverse field of a displacement field.
16460
itk::simple::InvertDisplacementField for the procedural interface
16462
itk::InvertDisplacementFieldImageFilter for the Doxygen on the original ITK class.
16465
C++ includes: sitkInvertDisplacementFieldImageFilter.h
16468
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::EnforceBoundaryConditionOff "
16471
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::EnforceBoundaryConditionOn "
16473
Set the value of EnforceBoundaryCondition to true or false
16478
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::Execute "
16480
Execute the filter on the input image
16484
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::Execute "
16486
Execute the filter on the input image with the given parameters
16490
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetEnforceBoundaryCondition "
16493
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetMaxErrorNorm "
16495
This is a measurement. Its value is updated in the Execute methods, so
16496
the value will only be valid after an execution.
16500
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetMaxErrorToleranceThreshold "
16503
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetMaximumNumberOfIterations "
16506
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetMeanErrorNorm "
16508
This is a measurement. Its value is updated in the Execute methods, so
16509
the value will only be valid after an execution.
16513
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetMeanErrorToleranceThreshold "
16516
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::GetName "
16522
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::InvertDisplacementFieldImageFilter "
16524
Default Constructor that takes no arguments and initializes default
16529
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::SetEnforceBoundaryCondition "
16532
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::SetMaxErrorToleranceThreshold "
16535
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::SetMaximumNumberOfIterations "
16538
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::SetMeanErrorToleranceThreshold "
16541
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::ToString "
16543
Print ourselves out
16547
%feature("docstring") itk::simple::InvertDisplacementFieldImageFilter::~InvertDisplacementFieldImageFilter "
16554
%feature("docstring") itk::simple::InvertIntensityImageFilter "
16556
Invert the intensity of an image.
16559
InvertIntensityImageFilter inverts intensity of pixels by subtracting pixel value to a maximum
16560
value. The maximum value can be set with SetMaximum and defaults the
16561
maximum of input pixel type. This filter can be used to invert, for
16562
example, a binary image, a distance map, etc.
16565
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
16566
de Jouy-en-Josas, France.
16569
IntensityWindowingImageFilter ShiftScaleImageFilter
16576
itk::simple::InvertIntensity for the procedural interface
16578
itk::InvertIntensityImageFilter for the Doxygen on the original ITK class.
16582
C++ includes: sitkInvertIntensityImageFilter.h
16585
%feature("docstring") itk::simple::InvertIntensityImageFilter::Execute "
16587
Execute the filter on the input image
16591
%feature("docstring") itk::simple::InvertIntensityImageFilter::Execute "
16593
Execute the filter on the input image with the given parameters
16597
%feature("docstring") itk::simple::InvertIntensityImageFilter::GetMaximum "
16599
Set/Get the maximum intensity value for the inversion.
16603
%feature("docstring") itk::simple::InvertIntensityImageFilter::GetName "
16609
%feature("docstring") itk::simple::InvertIntensityImageFilter::InvertIntensityImageFilter "
16611
Default Constructor that takes no arguments and initializes default
16616
%feature("docstring") itk::simple::InvertIntensityImageFilter::SetMaximum "
16618
Set/Get the maximum intensity value for the inversion.
16622
%feature("docstring") itk::simple::InvertIntensityImageFilter::ToString "
16624
Print ourselves out
16628
%feature("docstring") itk::simple::InvertIntensityImageFilter::~InvertIntensityImageFilter "
16635
%feature("docstring") itk::simple::IsoContourDistanceImageFilter "
16637
Compute an approximate distance from an interpolated isocontour to the
16641
For standard level set algorithms, it is useful to periodically
16642
reinitialize the evolving image to prevent numerical accuracy problems
16643
in computing derivatives. This reinitialization is done by computing a
16644
signed distance map to the current level set. This class provides the
16645
first step in this reinitialization by computing an estimate of the
16646
distance from the interpolated isocontour to the pixels (or voxels)
16647
that are close to it, i.e. for which the isocontour crosses a segment
16648
between them and one of their direct neighbors. This class supports
16649
narrowbanding. If the input narrowband is provided, the algorithm will
16650
only locate the level set within the input narrowband.
16652
Implementation of this class is based on Fast and Accurate
16653
Redistancing for Level Set Methods `Krissian K. and Westin C.F.',
16654
EUROCAST NeuroImaging Workshop Las Palmas Spain, Ninth International
16655
Conference on Computer Aided Systems Theory , pages 48-51, Feb 2003.
16657
itk::simple::IsoContourDistance for the procedural interface
16659
itk::IsoContourDistanceImageFilter for the Doxygen on the original ITK class.
16662
C++ includes: sitkIsoContourDistanceImageFilter.h
16665
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::Execute "
16667
Execute the filter on the input image
16671
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::Execute "
16673
Execute the filter on the input image with the given parameters
16677
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::GetFarValue "
16679
Set/Get the value of the level set to be located. The default value is
16684
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::GetLevelSetValue "
16686
Set/Get the value of the level set to be located. The default value is
16691
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::GetName "
16697
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::IsoContourDistanceImageFilter "
16699
Default Constructor that takes no arguments and initializes default
16704
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::SetFarValue "
16706
Set/Get the value of the level set to be located. The default value is
16711
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::SetLevelSetValue "
16713
Set/Get the value of the level set to be located. The default value is
16718
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::ToString "
16720
Print ourselves out
16724
%feature("docstring") itk::simple::IsoContourDistanceImageFilter::~IsoContourDistanceImageFilter "
16731
%feature("docstring") itk::simple::IsoDataThresholdImageFilter "
16733
Threshold an image using the IsoData Threshold.
16736
This filter creates a binary thresholded image that separates an image
16737
into foreground and background components. The filter computes the
16738
threshold using the IsoDataThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
16741
Richard Beare. Department of Medicine, Monash University, Melbourne,
16743
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
16744
de Jouy-en-Josas, France.
16746
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
16750
HistogramThresholdImageFilter
16752
itk::simple::IsoDataThreshold for the procedural interface
16754
itk::IsoDataThresholdImageFilter for the Doxygen on the original ITK class.
16757
C++ includes: sitkIsoDataThresholdImageFilter.h
16760
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::Execute "
16762
Execute the filter on the input image
16766
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::Execute "
16769
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::Execute "
16771
Execute the filter on the input image with the given parameters
16775
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::Execute "
16778
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetInsideValue "
16780
Get the \"inside\" pixel value.
16784
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetMaskOutput "
16787
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetMaskValue "
16790
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetName "
16796
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetNumberOfHistogramBins "
16799
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetOutsideValue "
16801
Get the \"outside\" pixel value.
16805
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::GetThreshold "
16807
Get the computed threshold.
16810
This is a measurement. Its value is updated in the Execute methods, so
16811
the value will only be valid after an execution.
16815
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::IsoDataThresholdImageFilter "
16817
Default Constructor that takes no arguments and initializes default
16822
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::MaskOutputOff "
16825
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::MaskOutputOn "
16827
Set the value of MaskOutput to true or false respectfully.
16831
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::SetInsideValue "
16833
Set the \"inside\" pixel value.
16837
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::SetMaskOutput "
16839
Do you want the output to be masked by the mask used in histogram
16840
construction. Only relevant if masking is in use.
16844
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::SetMaskValue "
16846
The value in the mask image, if used, indicating voxels that should be
16847
included. Default is the max of pixel type, as in the
16848
MaskedImageToHistogramFilter
16852
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::SetNumberOfHistogramBins "
16854
Set/Get the number of histogram bins.
16858
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::SetOutsideValue "
16860
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
16864
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::ToString "
16866
Print ourselves out
16870
%feature("docstring") itk::simple::IsoDataThresholdImageFilter::~IsoDataThresholdImageFilter "
16877
%feature("docstring") itk::simple::IsolatedConnectedImageFilter "
16879
Label pixels that are connected to one set of seeds but not another.
16882
IsolatedConnectedImageFilter finds the optimal threshold to separate two regions. It has two
16883
modes, one to separate dark regions surrounded by bright regions by
16884
automatically finding a minimum isolating upper threshold, and another
16885
to separate bright regions surrounded by dark regions by automatically
16886
finding a maximum lower isolating threshold. The mode can be chosen by
16887
setting FindUpperThresholdOn() /Off(). In both cases, the isolating threshold is retrieved with GetIsolatedValue() .
16889
The algorithm labels pixels with ReplaceValue that are connected to
16890
Seeds1 AND NOT connected to Seeds2. When finding the threshold to
16891
separate two dark regions surrounded by bright regions, given a fixed
16892
lower threshold, the filter adjusts the upper threshold until the two
16893
sets of seeds are not connected. The algorithm uses a binary search to
16894
adjust the upper threshold, starting at Upper. The reverse is true for
16895
finding the threshold to separate two bright regions. Lower defaults
16896
to the smallest possible value for the InputImagePixelType, and Upper
16897
defaults to the largest possible value for the InputImagePixelType.
16899
The user can also supply the Lower and Upper values to restrict the
16900
search. However, if the range is too restrictive, it could happen that
16901
no isolating threshold can be found between the user specified Lower
16902
and Upper values. Therefore, unless the user is sure of the bounds to
16903
set, it is recommended that the user set these values to the lowest
16904
and highest intensity values in the image, respectively.
16906
The user can specify more than one seed for both regions to separate.
16907
The algorithm will try find the threshold that ensures that all of the
16908
first seeds are contained in the resulting segmentation and all of the
16909
second seeds are not contained in the segmentation.
16911
It is possible that the algorithm may not be able to find the
16912
isolating threshold because no such threshold exists. The user can
16913
check for this by querying the GetThresholdingFailed() flag.
16915
itk::simple::IsolatedConnected for the procedural interface
16917
itk::IsolatedConnectedImageFilter for the Doxygen on the original ITK class.
16920
C++ includes: sitkIsolatedConnectedImageFilter.h
16923
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::Execute "
16925
Execute the filter on the input image
16929
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::Execute "
16931
Execute the filter on the input image with the given parameters
16935
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::FindUpperThresholdOff "
16938
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::FindUpperThresholdOn "
16940
Set the value of FindUpperThreshold to true or false respectfully.
16944
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetFindUpperThreshold "
16946
Set/Get whether to find an upper threshold (separating two dark
16947
regions) or a lower threshold (separating two bright regions).
16951
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetIsolatedValue "
16953
Get value that isolates the two seeds.
16955
This is a measurement. Its value is updated in the Execute methods, so
16956
the value will only be valid after an execution.
16960
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetIsolatedValueTolerance "
16962
Set/Get the precision required for the intensity threshold value. The
16967
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetLower "
16969
Set/Get the limit on the lower threshold value. The default is the
16970
NonpositiveMin() for the InputPixelType.
16974
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetName "
16980
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetReplaceValue "
16982
Set/Get value to replace thresholded pixels. Pixels that lie within
16983
the thresholds will be replaced with this value. The default is 1.
16987
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetSeed1 "
16990
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetSeed2 "
16993
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetThresholdingFailed "
16995
Get the flag that tells whether the algorithm failed to find a
16998
This is a measurement. Its value is updated in the Execute methods, so
16999
the value will only be valid after an execution.
17003
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::GetUpper "
17005
Set/Get the limit on the upper threshold value. The default is the
17006
max() for the InputPixelType.
17010
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::IsolatedConnectedImageFilter "
17012
Default Constructor that takes no arguments and initializes default
17017
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetFindUpperThreshold "
17019
Set/Get whether to find an upper threshold (separating two dark
17020
regions) or a lower threshold (separating two bright regions).
17024
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetIsolatedValueTolerance "
17026
Set/Get the precision required for the intensity threshold value. The
17031
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetLower "
17033
Set/Get the limit on the lower threshold value. The default is the
17034
NonpositiveMin() for the InputPixelType.
17038
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetReplaceValue "
17040
Set/Get value to replace thresholded pixels. Pixels that lie within
17041
the thresholds will be replaced with this value. The default is 1.
17045
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetSeed1 "
17047
DeprecatedSet seed point 1. This seed will be isolated from Seed2 (if
17048
possible). All pixels connected to this seed will be replaced with
17049
ReplaceValue. This method is deprecated, please use AddSeed1() .
17053
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetSeed2 "
17055
DeprecatedSet seed point 2. This seed will be isolated from Seed1 (if
17056
possible). This method is deprecated, please use AddSeed2() .
17060
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::SetUpper "
17062
Set/Get the limit on the upper threshold value. The default is the
17063
max() for the InputPixelType.
17067
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::ToString "
17069
Print ourselves out
17073
%feature("docstring") itk::simple::IsolatedConnectedImageFilter::~IsolatedConnectedImageFilter "
17080
%feature("docstring") itk::simple::IsolatedWatershedImageFilter "
17082
Isolate watershed basins using two seeds.
17085
IsolatedWatershedImageFilter labels pixels with ReplaceValue1 that are in the same watershed basin
17086
as Seed1 AND NOT the same as Seed2. The filter adjusts the waterlevel
17087
until the two seeds are not in different basins. The user supplies a
17088
Watershed threshold. The algorithm uses a binary search to adjust the
17089
upper waterlevel, starting at UpperValueLimit. UpperValueLimit
17090
defaults to the 1.0.
17092
itk::simple::IsolatedWatershed for the procedural interface
17094
itk::IsolatedWatershedImageFilter for the Doxygen on the original ITK class.
17097
C++ includes: sitkIsolatedWatershedImageFilter.h
17100
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::Execute "
17102
Execute the filter on the input image
17106
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::Execute "
17108
Execute the filter on the input image with the given parameters
17112
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetIsolatedValueTolerance "
17114
Set/Get the precision required for the intensity threshold value. The
17119
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetName "
17125
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetReplaceValue1 "
17127
Set/Get value to replace Seed1(Seed2) pixels, pixels that are within
17128
the basin that contains Seed1(Seed2) this value. The default is 1(0).
17132
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetReplaceValue2 "
17134
Set/Get value to replace Seed1(Seed2) pixels, pixels that are within
17135
the basin that contains Seed1(Seed2) this value. The default is 1(0).
17139
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetSeed1 "
17141
Set seed point 1. This seed will be isolated from Seed2 (if possible).
17142
All pixels connected to this seed will be replaced with ReplaceValue1.
17146
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetSeed2 "
17148
Set seed point 2. This seed will be isolated from Seed1 (if possible).
17149
All pixels connected to this seed will be replaced with ReplaceValue2.
17153
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetThreshold "
17155
Set/Get the Watershed threshold. The default is 0.
17159
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::GetUpperValueLimit "
17161
Set/Get the limit on the upper waterlevel value. The default is 1.0.
17165
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::IsolatedWatershedImageFilter "
17167
Default Constructor that takes no arguments and initializes default
17172
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetIsolatedValueTolerance "
17174
Set/Get the precision required for the intensity threshold value. The
17179
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetReplaceValue1 "
17181
Set/Get value to replace Seed1(Seed2) pixels, pixels that are within
17182
the basin that contains Seed1(Seed2) this value. The default is 1(0).
17186
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetReplaceValue2 "
17188
Set/Get value to replace Seed1(Seed2) pixels, pixels that are within
17189
the basin that contains Seed1(Seed2) this value. The default is 1(0).
17193
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetSeed1 "
17195
Set seed point 1. This seed will be isolated from Seed2 (if possible).
17196
All pixels connected to this seed will be replaced with ReplaceValue1.
17200
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetSeed2 "
17202
Set seed point 2. This seed will be isolated from Seed1 (if possible).
17203
All pixels connected to this seed will be replaced with ReplaceValue2.
17207
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetThreshold "
17209
Set/Get the Watershed threshold. The default is 0.
17213
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::SetUpperValueLimit "
17215
Set/Get the limit on the upper waterlevel value. The default is 1.0.
17219
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::ToString "
17221
Print ourselves out
17225
%feature("docstring") itk::simple::IsolatedWatershedImageFilter::~IsolatedWatershedImageFilter "
17232
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter "
17234
Computes the inverse of a displacement field.
17237
IterativeInverseDisplacementFieldImageFilter takes a displacement field as input and computes the displacement
17238
field that is its inverse. If the input displacement field was mapping
17239
coordinates from a space A into a space B, the output of this filter
17240
will map coordinates from the space B into the space A.
17242
The algorithm implemented in this filter uses an iterative method for
17243
progresively refining the values of the inverse field. Starting from
17244
the direct field, at every pixel the direct mapping of this point is
17245
found, and a the nevative of the current displacement is stored in the
17246
inverse field at the nearest pixel. Then, subsequent iterations verify
17247
if any of the neigbor pixels provide a better return to the current
17248
pixel, in which case its value is taken for updating the vector in the
17251
This method was discussed in the users-list during February 2004.
17257
itk::simple::IterativeInverseDisplacementField for the procedural interface
17259
itk::IterativeInverseDisplacementFieldImageFilter for the Doxygen on the original ITK class.
17262
C++ includes: sitkIterativeInverseDisplacementFieldImageFilter.h
17265
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::Execute "
17267
Execute the filter on the input image
17271
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::Execute "
17273
Execute the filter on the input image with the given parameters
17277
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::GetName "
17283
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::GetNumberOfIterations "
17286
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::GetStopValue "
17289
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::IterativeInverseDisplacementFieldImageFilter "
17291
Default Constructor that takes no arguments and initializes default
17296
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::SetNumberOfIterations "
17299
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::SetStopValue "
17302
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::ToString "
17304
Print ourselves out
17308
%feature("docstring") itk::simple::IterativeInverseDisplacementFieldImageFilter::~IterativeInverseDisplacementFieldImageFilter "
17315
%feature("docstring") itk::simple::JoinSeriesImageFilter "
17317
Join N-D images into an (N+1)-D image.
17320
This filter is templated over the input image type and the output
17321
image type. The pixel type of them must be the same and the input
17322
dimension must be less than the output dimension. When the input
17323
images are N-dimensinal, they are joined in order and the size of the
17324
N+1'th dimension of the output is same as the number of the inputs.
17325
The spacing and the origin (where the first input is placed) for the
17326
N+1'th dimension is specified in this filter. The output image
17327
informations for the first N dimensions are taken from the first
17328
input. Note that all the inputs should have the same information.
17332
Contributed in the users list http://public.kitware.com/pipermail/insight-
17333
users/2004-February/006542.html
17337
itk::simple::JoinSeries for the procedural interface
17340
C++ includes: sitkJoinSeriesImageFilter.h
17343
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17345
Execute the filter on the input images
17349
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17352
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17355
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17358
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17361
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17364
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17366
Execute the filter on the input images with the given parameters
17370
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17373
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17376
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17379
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17382
%feature("docstring") itk::simple::JoinSeriesImageFilter::Execute "
17385
%feature("docstring") itk::simple::JoinSeriesImageFilter::GetName "
17391
%feature("docstring") itk::simple::JoinSeriesImageFilter::GetOrigin "
17393
Set/Get origin of the new dimension
17397
%feature("docstring") itk::simple::JoinSeriesImageFilter::GetSpacing "
17399
Set/Get spacing of the new dimension
17403
%feature("docstring") itk::simple::JoinSeriesImageFilter::JoinSeriesImageFilter "
17405
Default Constructor that takes no arguments and initializes default
17410
%feature("docstring") itk::simple::JoinSeriesImageFilter::SetOrigin "
17412
Set/Get origin of the new dimension
17416
%feature("docstring") itk::simple::JoinSeriesImageFilter::SetSpacing "
17418
Set/Get spacing of the new dimension
17422
%feature("docstring") itk::simple::JoinSeriesImageFilter::ToString "
17424
Print ourselves out
17428
%feature("docstring") itk::simple::JoinSeriesImageFilter::~JoinSeriesImageFilter "
17435
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter "
17437
Threshold an image using the KittlerIllingworth Threshold.
17440
This filter creates a binary thresholded image that separates an image
17441
into foreground and background components. The filter computes the
17442
threshold using the KittlerIllingworthThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
17445
Richard Beare. Department of Medicine, Monash University, Melbourne,
17447
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
17448
de Jouy-en-Josas, France.
17450
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
17454
HistogramThresholdImageFilter
17456
itk::simple::KittlerIllingworthThreshold for the procedural interface
17458
itk::KittlerIllingworthThresholdImageFilter for the Doxygen on the original ITK class.
17461
C++ includes: sitkKittlerIllingworthThresholdImageFilter.h
17464
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::Execute "
17466
Execute the filter on the input image
17470
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::Execute "
17473
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::Execute "
17475
Execute the filter on the input image with the given parameters
17479
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::Execute "
17482
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetInsideValue "
17484
Get the \"inside\" pixel value.
17488
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetMaskOutput "
17491
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetMaskValue "
17494
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetName "
17500
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetNumberOfHistogramBins "
17503
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetOutsideValue "
17505
Get the \"outside\" pixel value.
17509
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::GetThreshold "
17511
Get the computed threshold.
17514
This is a measurement. Its value is updated in the Execute methods, so
17515
the value will only be valid after an execution.
17519
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::KittlerIllingworthThresholdImageFilter "
17521
Default Constructor that takes no arguments and initializes default
17526
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::MaskOutputOff "
17529
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::MaskOutputOn "
17531
Set the value of MaskOutput to true or false respectfully.
17535
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::SetInsideValue "
17537
Set the \"inside\" pixel value.
17541
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::SetMaskOutput "
17543
Do you want the output to be masked by the mask used in histogram
17544
construction. Only relevant if masking is in use.
17548
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::SetMaskValue "
17550
The value in the mask image, if used, indicating voxels that should be
17551
included. Default is the max of pixel type, as in the
17552
MaskedImageToHistogramFilter
17556
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::SetNumberOfHistogramBins "
17558
Set/Get the number of histogram bins.
17562
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::SetOutsideValue "
17564
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
17568
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::ToString "
17570
Print ourselves out
17574
%feature("docstring") itk::simple::KittlerIllingworthThresholdImageFilter::~KittlerIllingworthThresholdImageFilter "
17581
%feature("docstring") itk::simple::LabelContourImageFilter "
17583
Labels the pixels on the border of the objects in a labeled image.
17586
LabelContourImageFilter takes a labeled image as input, where the pixels in the objects are
17587
the pixels with a value different of the BackgroundValue. Only the
17588
pixels on the contours of the objects are kept. The pixels not on the
17589
border are changed to BackgroundValue. The labels of the object are
17590
the same in the input and in the output image.
17592
The connectivity can be changed to minimum or maximum connectivity
17593
with SetFullyConnected() . Full connectivity produces thicker contours.
17595
https://hdl.handle.net/1926/1352
17598
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
17599
de Jouy-en-Josas, France.
17602
BinaryContourImageFilter
17607
Label the contours of connected components
17609
itk::simple::LabelContour for the procedural interface
17611
itk::LabelContourImageFilter for the Doxygen on the original ITK class.
17615
C++ includes: sitkLabelContourImageFilter.h
17618
%feature("docstring") itk::simple::LabelContourImageFilter::Execute "
17620
Execute the filter on the input image
17624
%feature("docstring") itk::simple::LabelContourImageFilter::Execute "
17626
Execute the filter on the input image with the given parameters
17630
%feature("docstring") itk::simple::LabelContourImageFilter::FullyConnectedOff "
17633
%feature("docstring") itk::simple::LabelContourImageFilter::FullyConnectedOn "
17635
Set the value of FullyConnected to true or false respectfully.
17639
%feature("docstring") itk::simple::LabelContourImageFilter::GetBackgroundValue "
17641
Set/Get the background value used to identify the objects and mark the
17642
pixels not on the border of the objects.
17646
%feature("docstring") itk::simple::LabelContourImageFilter::GetFullyConnected "
17648
Set/Get whether the connected components are defined strictly by face
17649
connectivity or by face+edge+vertex connectivity. Default is
17651
For objects that are 1 pixel wide, use FullyConnectedOn.
17656
%feature("docstring") itk::simple::LabelContourImageFilter::GetName "
17662
%feature("docstring") itk::simple::LabelContourImageFilter::LabelContourImageFilter "
17664
Default Constructor that takes no arguments and initializes default
17669
%feature("docstring") itk::simple::LabelContourImageFilter::SetBackgroundValue "
17671
Set/Get the background value used to identify the objects and mark the
17672
pixels not on the border of the objects.
17676
%feature("docstring") itk::simple::LabelContourImageFilter::SetFullyConnected "
17678
Set/Get whether the connected components are defined strictly by face
17679
connectivity or by face+edge+vertex connectivity. Default is
17681
For objects that are 1 pixel wide, use FullyConnectedOn.
17686
%feature("docstring") itk::simple::LabelContourImageFilter::ToString "
17688
Print ourselves out
17692
%feature("docstring") itk::simple::LabelContourImageFilter::~LabelContourImageFilter "
17699
%feature("docstring") itk::simple::LabelImageToLabelMapFilter "
17701
convert a labeled image to a label collection image
17704
LabelImageToLabelMapFilter converts a label image to a label collection image. The labels are
17705
the same in the input and the output image.
17708
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
17709
de Jouy-en-Josas, France.
17710
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
17714
BinaryImageToLabelMapFilter , LabelMapToLabelImageFilter
17719
Convert an itk::Image consisting of labeled regions to a LabelMap
17721
itk::simple::LabelImageToLabelMapFilter for the procedural interface
17723
itk::LabelImageToLabelMapFilter for the Doxygen on the original ITK class.
17727
C++ includes: sitkLabelImageToLabelMapFilter.h
17730
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::Execute "
17732
Execute the filter on the input image
17736
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::Execute "
17738
Execute the filter on the input image with the given parameters
17742
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::GetBackgroundValue "
17744
Set/Get the value used as \"background\" in the output image. Defaults
17745
to NumericTraits<PixelType>::NonpositiveMin() .
17749
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::GetName "
17755
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::LabelImageToLabelMapFilter "
17757
Default Constructor that takes no arguments and initializes default
17762
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::SetBackgroundValue "
17764
Set/Get the value used as \"background\" in the output image. Defaults
17765
to NumericTraits<PixelType>::NonpositiveMin() .
17769
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::ToString "
17771
Print ourselves out
17775
%feature("docstring") itk::simple::LabelImageToLabelMapFilter::~LabelImageToLabelMapFilter "
17782
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter "
17784
a convenient class to convert a label image to a label map and valuate
17785
the statistics attributes at once
17789
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
17790
de Jouy-en-Josas, France.
17791
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
17795
StatisticsLabelObject , LabelStatisticsOpeningImageFilter , LabelStatisticsOpeningImageFilter
17797
itk::LabelImageToStatisticsLabelMapFilter for the Doxygen on the original ITK class.
17800
C++ includes: sitkLabelIntensityStatisticsImageFilter.h
17803
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::ComputeFeretDiameterOff "
17806
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::ComputeFeretDiameterOn "
17808
Set the value of ComputeFeretDiameter to true or false respectfully.
17812
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::ComputePerimeterOff "
17815
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::ComputePerimeterOn "
17817
Set the value of ComputePerimeter to true or false respectfully.
17821
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::Execute "
17823
Execute the filter on the input image
17827
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::Execute "
17829
Execute the filter on the input image with the given parameters
17833
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetBackgroundValue "
17835
Set/Get the value used as \"background\" in the output image. Defaults
17836
to NumericTraits<PixelType>::NonpositiveMin() .
17840
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetBoundingBox "
17842
This is an active measurement. It may be accessed while the filter is
17843
being executing in command call-backs and can be accessed after
17848
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetCenterOfGravity "
17850
This is an active measurement. It may be accessed while the filter is
17851
being executing in command call-backs and can be accessed after
17856
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetCentroid "
17858
This is an active measurement. It may be accessed while the filter is
17859
being executing in command call-backs and can be accessed after
17864
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetComputeFeretDiameter "
17866
Set/Get whether the maximum Feret diameter should be computed or not.
17867
The defaut value is false, because of the high computation time
17872
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetComputePerimeter "
17874
Set/Get whether the perimeter should be computed or not. The defaut
17875
value is false, because of the high computation time required.
17879
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetElongation "
17881
This is an active measurement. It may be accessed while the filter is
17882
being executing in command call-backs and can be accessed after
17887
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetEquivalentEllipsoidDiameter "
17889
This is an active measurement. It may be accessed while the filter is
17890
being executing in command call-backs and can be accessed after
17895
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetEquivalentSphericalPerimeter "
17897
This is an active measurement. It may be accessed while the filter is
17898
being executing in command call-backs and can be accessed after
17903
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetEquivalentSphericalRadius "
17905
This is an active measurement. It may be accessed while the filter is
17906
being executing in command call-backs and can be accessed after
17911
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetFeretDiameter "
17913
This is an active measurement. It may be accessed while the filter is
17914
being executing in command call-backs and can be accessed after
17919
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetFlatness "
17921
This is an active measurement. It may be accessed while the filter is
17922
being executing in command call-backs and can be accessed after
17927
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetKurtosis "
17929
This is an active measurement. It may be accessed while the filter is
17930
being executing in command call-backs and can be accessed after
17935
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetLabels "
17937
This is a measurement. Its value is updated in the Execute methods, so
17938
the value will only be valid after an execution.
17942
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMaximum "
17944
This is an active measurement. It may be accessed while the filter is
17945
being executing in command call-backs and can be accessed after
17950
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMaximumIndex "
17952
This is an active measurement. It may be accessed while the filter is
17953
being executing in command call-backs and can be accessed after
17958
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMean "
17960
This is an active measurement. It may be accessed while the filter is
17961
being executing in command call-backs and can be accessed after
17966
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMedian "
17968
This is an active measurement. It may be accessed while the filter is
17969
being executing in command call-backs and can be accessed after
17974
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMinimum "
17976
This is an active measurement. It may be accessed while the filter is
17977
being executing in command call-backs and can be accessed after
17982
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetMinimumIndex "
17984
This is an active measurement. It may be accessed while the filter is
17985
being executing in command call-backs and can be accessed after
17990
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetName "
17996
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetNumberOfBins "
17998
Set/Get the number of bins in the histogram. Note that the histogram
17999
is used to compute the median value, and that this option may have an
18000
effect on the value of the median.
18004
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetNumberOfLabels "
18006
Return the number of labels after execution.
18010
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetNumberOfPixels "
18012
This is an active measurement. It may be accessed while the filter is
18013
being executing in command call-backs and can be accessed after
18018
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetNumberOfPixelsOnBorder "
18020
This is an active measurement. It may be accessed while the filter is
18021
being executing in command call-backs and can be accessed after
18026
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPerimeter "
18028
This is an active measurement. It may be accessed while the filter is
18029
being executing in command call-backs and can be accessed after
18034
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPerimeterOnBorder "
18036
This is an active measurement. It may be accessed while the filter is
18037
being executing in command call-backs and can be accessed after
18042
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPerimeterOnBorderRatio "
18044
This is an active measurement. It may be accessed while the filter is
18045
being executing in command call-backs and can be accessed after
18050
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPhysicalSize "
18052
This is an active measurement. It may be accessed while the filter is
18053
being executing in command call-backs and can be accessed after
18058
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPrincipalAxes "
18060
This is an active measurement. It may be accessed while the filter is
18061
being executing in command call-backs and can be accessed after
18066
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetPrincipalMoments "
18068
This is an active measurement. It may be accessed while the filter is
18069
being executing in command call-backs and can be accessed after
18074
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetRoundness "
18076
This is an active measurement. It may be accessed while the filter is
18077
being executing in command call-backs and can be accessed after
18082
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetSkewness "
18084
This is an active measurement. It may be accessed while the filter is
18085
being executing in command call-backs and can be accessed after
18090
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetStandardDeviation "
18092
This is an active measurement. It may be accessed while the filter is
18093
being executing in command call-backs and can be accessed after
18098
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetSum "
18100
This is an active measurement. It may be accessed while the filter is
18101
being executing in command call-backs and can be accessed after
18106
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetVariance "
18108
This is an active measurement. It may be accessed while the filter is
18109
being executing in command call-backs and can be accessed after
18114
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetWeightedElongation "
18116
This is an active measurement. It may be accessed while the filter is
18117
being executing in command call-backs and can be accessed after
18122
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetWeightedFlatness "
18124
This is an active measurement. It may be accessed while the filter is
18125
being executing in command call-backs and can be accessed after
18130
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetWeightedPrincipalAxes "
18132
This is an active measurement. It may be accessed while the filter is
18133
being executing in command call-backs and can be accessed after
18138
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::GetWeightedPrincipalMoments "
18140
This is an active measurement. It may be accessed while the filter is
18141
being executing in command call-backs and can be accessed after
18146
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::HasLabel "
18148
Does the specified label exist? Can only be called after a call a call
18153
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::LabelIntensityStatisticsImageFilter "
18155
Default Constructor that takes no arguments and initializes default
18160
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::SetBackgroundValue "
18162
Set/Get the value used as \"background\" in the output image. Defaults
18163
to NumericTraits<PixelType>::NonpositiveMin() .
18167
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::SetComputeFeretDiameter "
18169
Set/Get whether the maximum Feret diameter should be computed or not.
18170
The defaut value is false, because of the high computation time
18175
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::SetComputePerimeter "
18177
Set/Get whether the perimeter should be computed or not. The defaut
18178
value is false, because of the high computation time required.
18182
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::SetNumberOfBins "
18184
Set/Get the number of bins in the histogram. Note that the histogram
18185
is used to compute the median value, and that this option may have an
18186
effect on the value of the median.
18190
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::ToString "
18192
Print ourselves out
18196
%feature("docstring") itk::simple::LabelIntensityStatisticsImageFilter::~LabelIntensityStatisticsImageFilter "
18203
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter "
18205
Apply a colormap to the contours (outlines) of each object in a label
18206
map and superimpose it on top of the feature image.
18209
The feature image is typically the image from which the labeling was
18210
produced. Use the SetInput function to set the LabelMap , and the SetFeatureImage function to set the feature image.
18212
Apply a colormap to a label map and put it on top of the input image.
18213
The set of colors is a good selection of distinct colors. The opacity
18214
of the label map can be defined by the user. A background label
18215
produce a gray pixel with the same intensity than the input one.
18218
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18219
de Jouy-en-Josas, France.
18220
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18224
LabelMapOverlayImageFilter , LabelOverlayImageFilter , LabelOverlayFunctor
18226
LabelMapToBinaryImageFilter , LabelMapToLabelImageFilter ,
18231
Color the boundaries of labeled regions in an image
18233
itk::simple::LabelMapContourOverlay for the procedural interface
18235
itk::LabelMapContourOverlayImageFilter for the Doxygen on the original ITK class.
18239
C++ includes: sitkLabelMapContourOverlayImageFilter.h
18242
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::Execute "
18244
Execute the filter on the input image
18248
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::Execute "
18250
Execute the filter on the input image with the given parameters
18254
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetColormap "
18257
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetContourThickness "
18259
Set/Get the contour thickness - 1 by default.
18263
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetContourType "
18265
Set/Get the overlay type - CONTOUR is used by default.
18269
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetDilationRadius "
18271
Set/Get the object dilation radius - 0 by default.
18275
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetName "
18281
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetOpacity "
18283
Set/Get the opacity of the colored label image. The value must be
18288
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetPriority "
18290
Set/Get the object priority - HIGH_LABEL_ON_TOP by default.
18294
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::GetSliceDimension "
18296
Set/Get the slice dimension - defaults to image dimension - 1.
18300
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::LabelMapContourOverlayImageFilter "
18302
Default Constructor that takes no arguments and initializes default
18307
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetColormap "
18310
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetContourThickness "
18312
Set/Get the contour thickness - 1 by default.
18316
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetContourType "
18318
Set/Get the overlay type - CONTOUR is used by default.
18322
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetDilationRadius "
18324
Set/Get the object dilation radius - 0 by default.
18328
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetDilationRadius "
18330
Set the values of the DilationRadius vector all to value
18334
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetOpacity "
18336
Set/Get the opacity of the colored label image. The value must be
18341
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetPriority "
18343
Set/Get the object priority - HIGH_LABEL_ON_TOP by default.
18347
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::SetSliceDimension "
18349
Set/Get the slice dimension - defaults to image dimension - 1.
18353
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::ToString "
18355
Print ourselves out
18359
%feature("docstring") itk::simple::LabelMapContourOverlayImageFilter::~LabelMapContourOverlayImageFilter "
18366
%feature("docstring") itk::simple::LabelMapMaskImageFilter "
18368
Mask and image with a LabelMap .
18371
LabelMapMaskImageFilter mask the content of an input image according to the content of the
18372
input LabelMap . The masked pixel of the input image are set to the BackgroundValue. LabelMapMaskImageFilter can keep the input image for one label only, with Negated = false
18373
(the default) or it can mask the input image for a single label, when
18374
Negated equals true. In Both cases, the label is set with SetLabel() .
18377
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18378
de Jouy-en-Josas, France.
18379
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18383
LabelMapToBinaryImageFilter , LabelMapToLabelImageFilter
18385
itk::simple::LabelMapMask for the procedural interface
18387
itk::LabelMapMaskImageFilter for the Doxygen on the original ITK class.
18390
C++ includes: sitkLabelMapMaskImageFilter.h
18393
%feature("docstring") itk::simple::LabelMapMaskImageFilter::CropOff "
18396
%feature("docstring") itk::simple::LabelMapMaskImageFilter::CropOn "
18398
Set the value of Crop to true or false respectfully.
18402
%feature("docstring") itk::simple::LabelMapMaskImageFilter::Execute "
18404
Execute the filter on the input image
18408
%feature("docstring") itk::simple::LabelMapMaskImageFilter::Execute "
18410
Execute the filter on the input image with the given parameters
18414
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetBackgroundValue "
18416
Set/Get the value used as \"background\" in the output image. Defaults
18417
to NumericTraits<PixelType>::ZeroValue() .
18421
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetCrop "
18423
Set/Get whether the image size should be adjusted to the masked image
18428
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetCropBorder "
18430
Set/Get the boder added to the mask before the crop. The default is 0
18435
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetLabel "
18437
The label to mask or to not mask, depending on the value of the
18442
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetName "
18448
%feature("docstring") itk::simple::LabelMapMaskImageFilter::GetNegated "
18450
Set/Get whether the Label should be masked or not.
18454
%feature("docstring") itk::simple::LabelMapMaskImageFilter::LabelMapMaskImageFilter "
18456
Default Constructor that takes no arguments and initializes default
18461
%feature("docstring") itk::simple::LabelMapMaskImageFilter::NegatedOff "
18464
%feature("docstring") itk::simple::LabelMapMaskImageFilter::NegatedOn "
18466
Set the value of Negated to true or false respectfully.
18470
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetBackgroundValue "
18472
Set/Get the value used as \"background\" in the output image. Defaults
18473
to NumericTraits<PixelType>::ZeroValue() .
18477
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetCrop "
18479
Set/Get whether the image size should be adjusted to the masked image
18484
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetCropBorder "
18486
Set/Get the boder added to the mask before the crop. The default is 0
18491
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetCropBorder "
18493
Set the values of the CropBorder vector all to value
18497
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetLabel "
18499
The label to mask or to not mask, depending on the value of the
18504
%feature("docstring") itk::simple::LabelMapMaskImageFilter::SetNegated "
18506
Set/Get whether the Label should be masked or not.
18510
%feature("docstring") itk::simple::LabelMapMaskImageFilter::ToString "
18512
Print ourselves out
18516
%feature("docstring") itk::simple::LabelMapMaskImageFilter::~LabelMapMaskImageFilter "
18523
%feature("docstring") itk::simple::LabelMapOverlayImageFilter "
18525
Apply a colormap to a label map and superimpose it on an image.
18528
Apply a colormap to a label map and put it on top of the feature
18529
image. The feature image is typically the image from which the
18530
labeling was produced. Use the SetInput function to set the LabelMap , and the SetFeatureImage function to set the feature image.
18532
The set of colors is a good selection of distinct colors. The opacity
18533
of the label map can be defined by the user. A background label
18534
produce a gray pixel with the same intensity than the input one.
18537
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18538
de Jouy-en-Josas, France.
18539
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18543
LabelOverlayImageFilter , LabelOverlayFunctor
18545
LabelMapToRGBImageFilter , LabelMapToBinaryImageFilter , LabelMapToLabelImageFilter
18547
itk::simple::LabelMapOverlay for the procedural interface
18549
itk::LabelMapOverlayImageFilter for the Doxygen on the original ITK class.
18552
C++ includes: sitkLabelMapOverlayImageFilter.h
18555
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::Execute "
18557
Execute the filter on the input image
18561
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::Execute "
18563
Execute the filter on the input image with the given parameters
18567
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::GetColormap "
18570
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::GetName "
18576
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::GetOpacity "
18578
Set/Get the opacity of the colored label image. The value must be
18583
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::LabelMapOverlayImageFilter "
18585
Default Constructor that takes no arguments and initializes default
18590
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::SetColormap "
18593
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::SetOpacity "
18595
Set/Get the opacity of the colored label image. The value must be
18600
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::ToString "
18602
Print ourselves out
18606
%feature("docstring") itk::simple::LabelMapOverlayImageFilter::~LabelMapOverlayImageFilter "
18613
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter "
18615
Convert a LabelMap to a binary image.
18618
LabelMapToBinaryImageFilter to a binary image. All the objects in the image are used as
18619
foreground. The background values of the original binary image can be
18620
restored by passing this image to the filter with the
18621
SetBackgroundImage() method.
18623
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18626
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18627
de Jouy-en-Josas, France.
18630
LabelMapToLabelImageFilter , LabelMapMaskImageFilter
18632
itk::simple::LabelMapToBinary for the procedural interface
18634
itk::LabelMapToBinaryImageFilter for the Doxygen on the original ITK class.
18637
C++ includes: sitkLabelMapToBinaryImageFilter.h
18640
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::Execute "
18642
Execute the filter on the input image
18646
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::Execute "
18648
Execute the filter on the input image with the given parameters
18652
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::GetBackgroundValue "
18654
Set/Get the value used as \"background\" in the output image. Defaults
18655
to NumericTraits<PixelType>::NonpositiveMin() .
18659
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::GetForegroundValue "
18661
Set/Get the value used as \"foreground\" in the output image. Defaults
18662
to NumericTraits<PixelType>::max() .
18666
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::GetName "
18672
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::LabelMapToBinaryImageFilter "
18674
Default Constructor that takes no arguments and initializes default
18679
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::SetBackgroundValue "
18681
Set/Get the value used as \"background\" in the output image. Defaults
18682
to NumericTraits<PixelType>::NonpositiveMin() .
18686
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::SetForegroundValue "
18688
Set/Get the value used as \"foreground\" in the output image. Defaults
18689
to NumericTraits<PixelType>::max() .
18693
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::ToString "
18695
Print ourselves out
18699
%feature("docstring") itk::simple::LabelMapToBinaryImageFilter::~LabelMapToBinaryImageFilter "
18706
%feature("docstring") itk::simple::LabelMapToLabelImageFilter "
18708
Converts a LabelMap to a labeled image.
18711
LabelMapToBinaryImageFilter to a label image.
18714
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18715
de Jouy-en-Josas, France.
18716
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18720
LabelMapToBinaryImageFilter , LabelMapMaskImageFilter
18725
Convert a LabelMap to a normal image with different values representing each region
18727
itk::simple::LabelMapToLabel for the procedural interface
18729
itk::LabelMapToLabelImageFilter for the Doxygen on the original ITK class.
18733
C++ includes: sitkLabelMapToLabelImageFilter.h
18736
%feature("docstring") itk::simple::LabelMapToLabelImageFilter::Execute "
18738
Execute the filter on the input image
18742
%feature("docstring") itk::simple::LabelMapToLabelImageFilter::GetName "
18748
%feature("docstring") itk::simple::LabelMapToLabelImageFilter::LabelMapToLabelImageFilter "
18750
Default Constructor that takes no arguments and initializes default
18755
%feature("docstring") itk::simple::LabelMapToLabelImageFilter::ToString "
18757
Print ourselves out
18761
%feature("docstring") itk::simple::LabelMapToLabelImageFilter::~LabelMapToLabelImageFilter "
18768
%feature("docstring") itk::simple::LabelMapToRGBImageFilter "
18770
Convert a LabelMap to a colored image.
18774
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18775
de Jouy-en-Josas, France.
18776
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
18780
LabelToRGBImageFilter , LabelToRGBFunctor
18782
LabelMapOverlayImageFilter , LabelMapToBinaryImageFilter , LabelMapMaskImageFilter
18784
itk::simple::LabelMapToRGB for the procedural interface
18786
itk::LabelMapToRGBImageFilter for the Doxygen on the original ITK class.
18789
C++ includes: sitkLabelMapToRGBImageFilter.h
18792
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::Execute "
18794
Execute the filter on the input image
18798
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::Execute "
18800
Execute the filter on the input image with the given parameters
18804
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::GetColormap "
18807
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::GetName "
18813
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::LabelMapToRGBImageFilter "
18815
Default Constructor that takes no arguments and initializes default
18820
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::SetColormap "
18823
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::ToString "
18825
Print ourselves out
18829
%feature("docstring") itk::simple::LabelMapToRGBImageFilter::~LabelMapToRGBImageFilter "
18836
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter "
18838
Computes overlap measures between the set same set of labels of pixels
18839
of two images. Background is assumed to be 0.
18842
This code was contributed in the Insight Journal paper: \"Introducing
18843
Dice, Jaccard, and Other Label Overlap Measures To ITK\" by Nicholas
18844
J. Tustison, James C. Gee https://hdl.handle.net/10380/3141 http://www.insight-journal.org/browse/publication/707
18847
Nicholas J. Tustison
18850
LabelOverlapMeasuresImageFilter
18852
itk::LabelOverlapMeasuresImageFilter for the Doxygen on the original ITK class.
18855
C++ includes: sitkLabelOverlapMeasuresImageFilter.h
18858
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::Execute "
18860
Execute the filter on the input images
18864
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetDiceCoefficient "
18866
Get the mean overlap (Dice coefficient) for the specified individual
18869
This is a measurement. Its value is updated in the Execute methods, so
18870
the value will only be valid after an execution.
18874
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetFalseNegativeError "
18876
Get the false negative error for the specified individual label.
18878
This is a measurement. Its value is updated in the Execute methods, so
18879
the value will only be valid after an execution.
18883
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetFalsePositiveError "
18885
Get the false positive error for the specified individual label.
18887
This is a measurement. Its value is updated in the Execute methods, so
18888
the value will only be valid after an execution.
18892
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetJaccardCoefficient "
18894
Get the union overlap (Jaccard coefficient) for the specified
18897
This is a measurement. Its value is updated in the Execute methods, so
18898
the value will only be valid after an execution.
18902
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetMeanOverlap "
18904
Get the mean overlap (Dice coefficient) for the specified individual
18907
This is a measurement. Its value is updated in the Execute methods, so
18908
the value will only be valid after an execution.
18912
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetName "
18918
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetUnionOverlap "
18920
Get the union overlap (Jaccard coefficient) for the specified
18923
This is a measurement. Its value is updated in the Execute methods, so
18924
the value will only be valid after an execution.
18928
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::GetVolumeSimilarity "
18930
Get the volume similarity for the specified individual label.
18932
This is a measurement. Its value is updated in the Execute methods, so
18933
the value will only be valid after an execution.
18937
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::LabelOverlapMeasuresImageFilter "
18939
Default Constructor that takes no arguments and initializes default
18944
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::ToString "
18946
Print ourselves out
18950
%feature("docstring") itk::simple::LabelOverlapMeasuresImageFilter::~LabelOverlapMeasuresImageFilter "
18957
%feature("docstring") itk::simple::LabelOverlayImageFilter "
18959
Apply a colormap to a label image and put it on top of the input
18963
Apply a colormap to a label image and put it on top of the input
18964
image. The set of colors is a good selection of distinct colors. The
18965
opacity of the label image can be defined by the user. The user can
18966
also choose if the want to use a background and which label value is
18967
the background. A background label produce a gray pixel with the same
18968
intensity than the input one.
18971
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
18972
de Jouy-en-Josas, France.
18973
This class was contributed to the Insight Journal https://hdl.handle.net/1926/172
18977
LabelToRGBImageFilter
18979
LabelMapOverlayImageFilter , LabelOverlayFunctor
18984
Overlay a LabelMap on an image
18986
itk::simple::LabelOverlay for the procedural interface
18988
itk::LabelOverlayImageFilter for the Doxygen on the original ITK class.
18992
C++ includes: sitkLabelOverlayImageFilter.h
18995
%feature("docstring") itk::simple::LabelOverlayImageFilter::Execute "
18997
Execute the filter on the input image
19001
%feature("docstring") itk::simple::LabelOverlayImageFilter::Execute "
19003
Execute the filter on the input image with the given parameters
19007
%feature("docstring") itk::simple::LabelOverlayImageFilter::GetBackgroundValue "
19009
Set/Get the background value
19013
%feature("docstring") itk::simple::LabelOverlayImageFilter::GetColormap "
19016
%feature("docstring") itk::simple::LabelOverlayImageFilter::GetName "
19022
%feature("docstring") itk::simple::LabelOverlayImageFilter::GetOpacity "
19024
Set/Get the opacity of the colored label image. The value must be
19029
%feature("docstring") itk::simple::LabelOverlayImageFilter::LabelOverlayImageFilter "
19031
Default Constructor that takes no arguments and initializes default
19036
%feature("docstring") itk::simple::LabelOverlayImageFilter::SetBackgroundValue "
19038
Set/Get the background value
19042
%feature("docstring") itk::simple::LabelOverlayImageFilter::SetColormap "
19045
%feature("docstring") itk::simple::LabelOverlayImageFilter::SetOpacity "
19047
Set/Get the opacity of the colored label image. The value must be
19052
%feature("docstring") itk::simple::LabelOverlayImageFilter::ToString "
19054
Print ourselves out
19058
%feature("docstring") itk::simple::LabelOverlayImageFilter::~LabelOverlayImageFilter "
19065
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter "
19067
Converts a label image to a label map and valuates the shape
19071
A convenient class that converts a label image to a label map and
19072
valuates the shape attribute at once.
19074
This implementation was taken from the Insight Journal paper:
19076
https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
19079
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
19080
de Jouy-en-Josas, France.
19083
ShapeLabelObject , LabelShapeOpeningImageFilter , LabelStatisticsOpeningImageFilter
19088
Convert an itk::Image consisting of labeled regions to a ShapeLabelMap
19091
itk::LabelImageToShapeLabelMapFilter for the Doxygen on the original ITK class.
19094
C++ includes: sitkLabelShapeStatisticsImageFilter.h
19097
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::ComputeFeretDiameterOff "
19100
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::ComputeFeretDiameterOn "
19102
Set the value of ComputeFeretDiameter to true or false respectfully.
19106
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::ComputePerimeterOff "
19109
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::ComputePerimeterOn "
19111
Set the value of ComputePerimeter to true or false respectfully.
19115
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::Execute "
19117
Execute the filter on the input image
19121
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::Execute "
19123
Execute the filter on the input image with the given parameters
19127
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetBackgroundValue "
19129
Set/Get the value used as \"background\" in the output image. Defaults
19130
to NumericTraits<PixelType>::NonpositiveMin() .
19134
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetBoundingBox "
19136
This is an active measurement. It may be accessed while the filter is
19137
being executing in command call-backs and can be accessed after
19142
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetCentroid "
19144
This is an active measurement. It may be accessed while the filter is
19145
being executing in command call-backs and can be accessed after
19150
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetComputeFeretDiameter "
19152
Set/Get whether the maximum Feret diameter should be computed or not.
19153
Default value is false, because of the high computation time required.
19157
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetComputePerimeter "
19159
Set/Get whether the perimeter should be computed or not. Default value
19160
is false, because of the high computation time required.
19164
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetElongation "
19166
This is an active measurement. It may be accessed while the filter is
19167
being executing in command call-backs and can be accessed after
19172
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetEquivalentEllipsoidDiameter "
19174
This is an active measurement. It may be accessed while the filter is
19175
being executing in command call-backs and can be accessed after
19180
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetEquivalentSphericalPerimeter "
19182
This is an active measurement. It may be accessed while the filter is
19183
being executing in command call-backs and can be accessed after
19188
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetEquivalentSphericalRadius "
19190
This is an active measurement. It may be accessed while the filter is
19191
being executing in command call-backs and can be accessed after
19196
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetFeretDiameter "
19198
This is an active measurement. It may be accessed while the filter is
19199
being executing in command call-backs and can be accessed after
19204
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetFlatness "
19206
This is an active measurement. It may be accessed while the filter is
19207
being executing in command call-backs and can be accessed after
19212
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetLabels "
19214
This is a measurement. Its value is updated in the Execute methods, so
19215
the value will only be valid after an execution.
19219
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetName "
19225
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetNumberOfLabels "
19227
Return the number of labels after execution.
19231
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetNumberOfPixels "
19233
This is an active measurement. It may be accessed while the filter is
19234
being executing in command call-backs and can be accessed after
19239
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetNumberOfPixelsOnBorder "
19241
This is an active measurement. It may be accessed while the filter is
19242
being executing in command call-backs and can be accessed after
19247
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPerimeter "
19249
This is an active measurement. It may be accessed while the filter is
19250
being executing in command call-backs and can be accessed after
19255
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPerimeterOnBorder "
19257
This is an active measurement. It may be accessed while the filter is
19258
being executing in command call-backs and can be accessed after
19263
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPerimeterOnBorderRatio "
19265
This is an active measurement. It may be accessed while the filter is
19266
being executing in command call-backs and can be accessed after
19271
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPhysicalSize "
19273
This is an active measurement. It may be accessed while the filter is
19274
being executing in command call-backs and can be accessed after
19279
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPrincipalAxes "
19281
This is an active measurement. It may be accessed while the filter is
19282
being executing in command call-backs and can be accessed after
19287
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetPrincipalMoments "
19289
This is an active measurement. It may be accessed while the filter is
19290
being executing in command call-backs and can be accessed after
19295
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::GetRoundness "
19297
This is an active measurement. It may be accessed while the filter is
19298
being executing in command call-backs and can be accessed after
19303
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::HasLabel "
19305
Does the specified label exist? Can only be called after a call a call
19310
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::LabelShapeStatisticsImageFilter "
19312
Default Constructor that takes no arguments and initializes default
19317
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::SetBackgroundValue "
19319
Set/Get the value used as \"background\" in the output image. Defaults
19320
to NumericTraits<PixelType>::NonpositiveMin() .
19324
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::SetComputeFeretDiameter "
19326
Set/Get whether the maximum Feret diameter should be computed or not.
19327
Default value is false, because of the high computation time required.
19331
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::SetComputePerimeter "
19333
Set/Get whether the perimeter should be computed or not. Default value
19334
is false, because of the high computation time required.
19338
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::ToString "
19340
Print ourselves out
19344
%feature("docstring") itk::simple::LabelShapeStatisticsImageFilter::~LabelShapeStatisticsImageFilter "
19351
%feature("docstring") itk::simple::LabelStatisticsImageFilter "
19353
Given an intensity image and a label map, compute min, max, variance
19354
and mean of the pixels associated with each label or segment.
19357
LabelStatisticsImageFilter computes the minimum, maximum, sum, mean, median, variance and sigma
19358
of regions of an intensity image, where the regions are defined via a
19359
label map (a second input). The label image should be integral type.
19360
The filter needs all of its input image. It behaves as a filter with
19361
an input and output. Thus it can be inserted in a pipline with other
19362
filters and the statistics will only be recomputed if a downstream
19365
Optionally, the filter also computes intensity histograms on each
19366
object. If histograms are enabled, a median intensity value can also
19367
be computed, although its accuracy is limited to the bin width of the
19368
histogram. If histograms are not enabled, the median returns zero.
19370
The filter passes its intensity input through unmodified. The filter
19371
is threaded. It computes statistics in each thread then combines them
19372
in its AfterThreadedGenerate method.
19378
Get statistical properties of labeled regions in an image
19381
itk::LabelStatisticsImageFilter for the Doxygen on the original ITK class.
19384
C++ includes: sitkLabelStatisticsImageFilter.h
19387
%feature("docstring") itk::simple::LabelStatisticsImageFilter::Execute "
19389
Execute the filter on the input image
19393
%feature("docstring") itk::simple::LabelStatisticsImageFilter::Execute "
19395
Execute the filter on the input image with the given parameters
19399
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetBoundingBox "
19401
Return the computed bounding box for a label.
19403
This is an active measurement. It may be accessed while the filter is
19404
being executing in command call-backs and can be accessed after
19409
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetCount "
19411
Return the number of pixels for a label.
19413
This is an active measurement. It may be accessed while the filter is
19414
being executing in command call-backs and can be accessed after
19419
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetLabels "
19421
This is a measurement. Its value is updated in the Execute methods, so
19422
the value will only be valid after an execution.
19426
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetMaximum "
19428
Return the computed Maximum for a label.
19430
This is an active measurement. It may be accessed while the filter is
19431
being executing in command call-backs and can be accessed after
19436
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetMean "
19438
Return the computed Mean for a label.
19440
This is an active measurement. It may be accessed while the filter is
19441
being executing in command call-backs and can be accessed after
19446
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetMedian "
19448
Return the computed Median for a label. Requires histograms to be
19451
This is an active measurement. It may be accessed while the filter is
19452
being executing in command call-backs and can be accessed after
19457
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetMinimum "
19459
Return the computed Minimum for a label.
19461
This is an active measurement. It may be accessed while the filter is
19462
being executing in command call-backs and can be accessed after
19467
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetName "
19473
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetNumberOfLabels "
19475
Return the number of labels after execution .
19479
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetSigma "
19481
Return the computed Standard Deviation for a label.
19483
This is an active measurement. It may be accessed while the filter is
19484
being executing in command call-backs and can be accessed after
19489
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetSum "
19491
Return the compute Sum for a label.
19493
This is an active measurement. It may be accessed while the filter is
19494
being executing in command call-backs and can be accessed after
19499
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetUseHistograms "
19502
%feature("docstring") itk::simple::LabelStatisticsImageFilter::GetVariance "
19504
Return the computed Variance for a label.
19506
This is an active measurement. It may be accessed while the filter is
19507
being executing in command call-backs and can be accessed after
19512
%feature("docstring") itk::simple::LabelStatisticsImageFilter::HasLabel "
19514
Does the specified label exist? Can only be called after a call a call
19519
%feature("docstring") itk::simple::LabelStatisticsImageFilter::LabelStatisticsImageFilter "
19521
Default Constructor that takes no arguments and initializes default
19526
%feature("docstring") itk::simple::LabelStatisticsImageFilter::SetUseHistograms "
19529
%feature("docstring") itk::simple::LabelStatisticsImageFilter::ToString "
19531
Print ourselves out
19535
%feature("docstring") itk::simple::LabelStatisticsImageFilter::UseHistogramsOff "
19538
%feature("docstring") itk::simple::LabelStatisticsImageFilter::UseHistogramsOn "
19540
Set the value of UseHistograms to true or false respectfully.
19544
%feature("docstring") itk::simple::LabelStatisticsImageFilter::~LabelStatisticsImageFilter "
19551
%feature("docstring") itk::simple::LabelToRGBImageFilter "
19553
Apply a colormap to a label image.
19556
Apply a colormap to a label image. The set of colors is a good
19557
selection of distinct colors. The user can choose to use a background
19558
value. In that case, a gray pixel with the same intensity than the
19559
background label is produced.
19561
This code was contributed in the Insight Journal paper: \"The
19562
watershed transform in ITK - discussion and new developments\" by
19563
Beare R., Lehmann G. https://hdl.handle.net/1926/202 http://www.insight-journal.org/browse/publication/92
19566
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
19567
de Jouy-en-Josas, France.
19568
Richard Beare. Department of Medicine, Monash University, Melbourne,
19573
LabelOverlayImageFilter
19575
LabelMapToRGBImageFilter , LabelToRGBFunctor, ScalarToRGBPixelFunctor
19577
itk::simple::LabelToRGB for the procedural interface
19579
itk::LabelToRGBImageFilter for the Doxygen on the original ITK class.
19582
C++ includes: sitkLabelToRGBImageFilter.h
19585
%feature("docstring") itk::simple::LabelToRGBImageFilter::Execute "
19587
Execute the filter on the input image
19591
%feature("docstring") itk::simple::LabelToRGBImageFilter::Execute "
19593
Execute the filter on the input image with the given parameters
19597
%feature("docstring") itk::simple::LabelToRGBImageFilter::GetBackgroundValue "
19599
Set/Get the background value
19603
%feature("docstring") itk::simple::LabelToRGBImageFilter::GetColormap "
19606
%feature("docstring") itk::simple::LabelToRGBImageFilter::GetName "
19612
%feature("docstring") itk::simple::LabelToRGBImageFilter::LabelToRGBImageFilter "
19614
Default Constructor that takes no arguments and initializes default
19619
%feature("docstring") itk::simple::LabelToRGBImageFilter::SetBackgroundValue "
19621
Set/Get the background value
19625
%feature("docstring") itk::simple::LabelToRGBImageFilter::SetColormap "
19628
%feature("docstring") itk::simple::LabelToRGBImageFilter::ToString "
19630
Print ourselves out
19634
%feature("docstring") itk::simple::LabelToRGBImageFilter::~LabelToRGBImageFilter "
19641
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter "
19643
Make sure that the objects are not overlapping.
19646
AttributeUniqueLabelMapFilter search the overlapping zones in the overlapping objects and keeps
19647
only a single object on all the pixels of the image. The object to
19648
keep is selected according to their label.
19651
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
19652
de Jouy-en-Josas, France.
19653
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
19657
AttributeLabelObject
19659
itk::simple::LabelUniqueLabelMapFilter for the procedural interface
19661
itk::LabelUniqueLabelMapFilter for the Doxygen on the original ITK class.
19664
C++ includes: sitkLabelUniqueLabelMapFilter.h
19667
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::Execute "
19669
Execute the filter on the input image
19673
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::Execute "
19675
Execute the filter on the input image with the given parameters
19679
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::GetName "
19685
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::GetReverseOrdering "
19688
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::LabelUniqueLabelMapFilter "
19690
Default Constructor that takes no arguments and initializes default
19695
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::ReverseOrderingOff "
19698
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::ReverseOrderingOn "
19700
Set the value of ReverseOrdering to true or false respectfully.
19704
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::SetReverseOrdering "
19707
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::ToString "
19709
Print ourselves out
19713
%feature("docstring") itk::simple::LabelUniqueLabelMapFilter::~LabelUniqueLabelMapFilter "
19720
%feature("docstring") itk::simple::LabelVotingImageFilter "
19722
This filter performs pixelwise voting among an arbitrary number of
19723
input images, where each of them represents a segmentation of the same
19724
scene (i.e., image).
19727
Label voting is a simple method of classifier combination applied to
19728
image segmentation. Typically, the accuracy of the combined
19729
segmentation exceeds the accuracy of any of the input segmentations.
19730
Voting is therefore commonly used as a way of boosting segmentation
19733
The use of label voting for combination of multiple segmentations is
19736
T. Rohlfing and C. R. Maurer, Jr., \"Multi-classifier framework for
19737
atlas-based image segmentation,\" Pattern Recognition Letters, 2005.
19740
All input volumes to this filter must be segmentations of an image,
19741
that is, they must have discrete pixel values where each value
19742
represents a different segmented object.
19743
Input volumes must all contain the same size RequestedRegions. Not all input images must contain all possible labels, but all label
19744
values must have the same meaning in all images.
19747
The voting filter produces a single output volume. Each output pixel
19748
contains the label that occurred most often among the labels assigned
19749
to this pixel in all the input volumes, that is, the label that
19750
received the maximum number of \"votes\" from the input pixels.. If
19751
the maximum number of votes is not unique, i.e., if more than one
19752
label have a maximum number of votes, an \"undecided\" label is
19753
assigned to that output pixel.
19754
By default, the label used for undecided pixels is the maximum label
19755
value used in the input images plus one. Since it is possible for an
19756
image with 8 bit pixel values to use all 256 possible label values, it
19757
is permissible to combine 8 bit (i.e., byte) images into a 16 bit
19758
(i.e., short) output image.
19761
The label used for \"undecided\" labels can be set using
19762
SetLabelForUndecidedPixels. This functionality can be unset by calling
19763
UnsetLabelForUndecidedPixels.
19765
Torsten Rohlfing, SRI International, Neuroscience Program
19768
itk::simple::LabelVoting for the procedural interface
19771
C++ includes: sitkLabelVotingImageFilter.h
19774
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19776
Execute the filter on the input images
19780
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19783
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19786
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19789
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19792
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19795
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19797
Execute the filter on the input images with the given parameters
19801
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19804
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19807
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19810
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19813
%feature("docstring") itk::simple::LabelVotingImageFilter::Execute "
19816
%feature("docstring") itk::simple::LabelVotingImageFilter::GetLabelForUndecidedPixels "
19818
Get label value used for undecided pixels. After updating the filter,
19819
this function returns the actual label value used for undecided pixels
19820
in the current output. Note that this value is overwritten when
19821
SetLabelForUndecidedPixels is called and the new value only becomes
19822
effective upon the next filter update.
19826
%feature("docstring") itk::simple::LabelVotingImageFilter::GetName "
19832
%feature("docstring") itk::simple::LabelVotingImageFilter::LabelVotingImageFilter "
19834
Default Constructor that takes no arguments and initializes default
19839
%feature("docstring") itk::simple::LabelVotingImageFilter::SetLabelForUndecidedPixels "
19841
Set label value for undecided pixels.
19845
%feature("docstring") itk::simple::LabelVotingImageFilter::ToString "
19847
Print ourselves out
19851
%feature("docstring") itk::simple::LabelVotingImageFilter::~LabelVotingImageFilter "
19858
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter "
19860
This class computes the transform that aligns the fixed and moving
19861
images given a set of pair landmarks. The class is templated over the Transform type as well as fixed image and moving image types. The transform
19862
computed gives the best fit transform that maps the fixed and moving
19863
images in a least squares sense. The indices are taken to correspond,
19864
so point 1 in the first set will get mapped close to point 1 in the
19867
Currently, the following transforms are supported by the class: VersorRigid3DTransform Rigid2DTransform AffineTransform BSplineTransform
19869
An equal number of fixed and moving landmarks need to be specified
19870
using SetFixedLandmarks() and SetMovingLandmarks() . Any number of landmarks may be specified. In the case of using
19871
Affine or BSpline transforms, each landmark pair can contribute in the
19872
final transform based on its defined weight. Number of weights should
19873
be equal to the number of landmarks and can be specified using SetLandmarkWeight() . By defaults are weights are set to one. Call InitializeTransform()
19874
to initialize the transform.
19876
The class is based in part on Hybrid/vtkLandmarkTransform originally
19877
implemented in python by David G. Gobbi.
19879
The solution is based on Berthold K. P. Horn (1987), \"Closed-form
19880
solution of absolute orientation using unit quaternions,\" http://people.csail.mit.edu/bkph/papers/Absolute_Orientation.pdf
19882
The Affine Transform initializer is based on an algorithm by H Spaeth, and is described in
19883
the Insight Journal Article \"Affine Transformation for Landmark Based
19884
Registration Initializer in ITK\" by Kim E.Y., Johnson H., Williams N.
19885
available at http://midasjournal.com/browse/publication/825
19891
Rigidly register one image to another using manually specified
19894
itk::simple::LandmarkBasedTransformInitializerFilter for the procedural interface
19896
itk::LandmarkBasedTransformInitializer for the Doxygen on the original ITK class.
19900
C++ includes: sitkLandmarkBasedTransformInitializerFilter.h
19903
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::Execute "
19905
Execute the filter on the input image
19909
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::Execute "
19911
Execute the filter on the input image with the given parameters
19915
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetBSplineNumberOfControlPoints "
19917
Set/Get the number of control points
19921
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetFixedLandmarks "
19924
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetLandmarkWeight "
19927
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetMovingLandmarks "
19929
Get the shrink factors.
19933
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetName "
19939
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::GetReferenceImage "
19942
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::LandmarkBasedTransformInitializerFilter "
19944
Default Constructor that takes no arguments and initializes default
19949
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::SetBSplineNumberOfControlPoints "
19951
Set/Get the number of control points
19955
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::SetFixedLandmarks "
19957
Set the Fixed landmark point containers
19961
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::SetLandmarkWeight "
19963
Set the landmark weight point containers Weight includes diagonal
19964
elements of weight matrix
19968
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::SetMovingLandmarks "
19970
Set the Moving landmark point containers
19974
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::SetReferenceImage "
19976
Set the reference image to define the parametric domain for the
19981
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::ToString "
19983
Print ourselves out
19987
%feature("docstring") itk::simple::LandmarkBasedTransformInitializerFilter::~LandmarkBasedTransformInitializerFilter "
19994
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter "
19996
Deconvolve an image using the Landweber deconvolution algorithm.
19999
This filter implements the Landweber deconvolution algorthm as defined
20000
in Bertero M and Boccacci P, \"Introduction to Inverse Problems in
20001
Imaging\", 1998. The algorithm assumes that the input image has been
20002
formed by a linear shift-invariant system with a known kernel.
20004
The Landweber algorithm converges to a solution that minimizes the sum
20005
of squared errors $||f \\\\otimes h - g||$ where $f$ is the estimate of the unblurred image, $\\\\otimes$ is the convolution operator, $h$ is the blurring kernel, and $g$ is the blurred input image. As such, it is best suited for images
20006
that have zero-mean Gaussian white noise.
20008
This is the base implementation of the Landweber algorithm. It may
20009
produce results with negative values. For a version of this algorithm
20010
that enforces a positivity constraint on each intermediate solution,
20011
see ProjectedLandweberDeconvolutionImageFilter .
20013
This code was adapted from the Insight Journal contribution:
20015
\"Deconvolution: infrastructure and reference algorithms\" by Gaetan
20016
Lehmann https://hdl.handle.net/10380/3207
20019
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
20020
de Jouy-en-Josas, France
20021
Cory Quammen, The University of North Carolina at Chapel Hill
20025
IterativeDeconvolutionImageFilter
20027
RichardsonLucyDeconvolutionImageFilter
20029
ProjectedLandweberDeconvolutionImageFilter
20031
itk::simple::LandweberDeconvolution for the procedural interface
20033
itk::LandweberDeconvolutionImageFilter for the Doxygen on the original ITK class.
20036
C++ includes: sitkLandweberDeconvolutionImageFilter.h
20039
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::Execute "
20041
Execute the filter on the input images
20045
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::Execute "
20047
Execute the filter on the input images with the given parameters
20051
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetAlpha "
20053
Set/get relaxation factor.
20057
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetBoundaryCondition "
20060
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetName "
20066
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetNormalize "
20069
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetNumberOfIterations "
20071
Get the number of iterations.
20075
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::GetOutputRegionMode "
20078
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::LandweberDeconvolutionImageFilter "
20080
Default Constructor that takes no arguments and initializes default
20085
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::NormalizeOff "
20088
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::NormalizeOn "
20090
Set the value of Normalize to true or false respectfully.
20094
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::SetAlpha "
20096
Set/get relaxation factor.
20100
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::SetBoundaryCondition "
20103
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::SetNormalize "
20105
Normalize the output image by the sum of the kernel components
20109
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::SetNumberOfIterations "
20111
Set the number of iterations.
20115
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::SetOutputRegionMode "
20118
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::ToString "
20120
Print ourselves out
20124
%feature("docstring") itk::simple::LandweberDeconvolutionImageFilter::~LandweberDeconvolutionImageFilter "
20131
%feature("docstring") itk::simple::LaplacianImageFilter "
20133
This filter computes the Laplacian of a scalar-valued image. The
20134
Laplacian is an isotropic measure of the 2nd spatial derivative of an
20135
image. The Laplacian of an image highlights regions of rapid intensity
20136
change and is therefore often used for edge detection. Often, the
20137
Laplacian is applied to an image that has first been smoothed with a
20138
Gaussian filter in order to reduce its sensitivity to noise.
20141
The Laplacian at each pixel location is computed by convolution with
20142
the itk::LaplacianOperator .
20144
The input to this filter is a scalar-valued itk::Image of arbitrary dimension. The output is a scalar-valued itk::Image .
20147
The pixel type of the input and output images must be of real type
20148
(float or double). ConceptChecking is used here to enforce the input
20149
pixel type. You will get a compilation error if the pixel type of the
20150
input and output images is not float or double.
20157
NeighborhoodOperator
20159
NeighborhoodIterator
20166
Compute the Laplacian of an image
20168
itk::simple::Laplacian for the procedural interface
20170
itk::LaplacianImageFilter for the Doxygen on the original ITK class.
20174
C++ includes: sitkLaplacianImageFilter.h
20177
%feature("docstring") itk::simple::LaplacianImageFilter::Execute "
20179
Execute the filter on the input image
20183
%feature("docstring") itk::simple::LaplacianImageFilter::Execute "
20185
Execute the filter on the input image with the given parameters
20189
%feature("docstring") itk::simple::LaplacianImageFilter::GetName "
20195
%feature("docstring") itk::simple::LaplacianImageFilter::GetUseImageSpacing "
20197
Set/Get whether or not the filter will use the spacing of the input
20198
image in its calculations
20202
%feature("docstring") itk::simple::LaplacianImageFilter::LaplacianImageFilter "
20204
Default Constructor that takes no arguments and initializes default
20209
%feature("docstring") itk::simple::LaplacianImageFilter::SetUseImageSpacing "
20211
Set/Get whether or not the filter will use the spacing of the input
20212
image in its calculations
20216
%feature("docstring") itk::simple::LaplacianImageFilter::ToString "
20218
Print ourselves out
20222
%feature("docstring") itk::simple::LaplacianImageFilter::UseImageSpacingOff "
20225
%feature("docstring") itk::simple::LaplacianImageFilter::UseImageSpacingOn "
20227
Set the value of UseImageSpacing to true or false respectfully.
20231
%feature("docstring") itk::simple::LaplacianImageFilter::~LaplacianImageFilter "
20238
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter "
20240
Computes the Laplacian of Gaussian (LoG) of an image.
20243
Computes the Laplacian of Gaussian (LoG) of an image by convolution
20244
with the second derivative of a Gaussian. This filter is implemented
20245
using the recursive gaussian filters.
20251
Compute the Laplacian of Gaussian (LoG) of an image
20253
itk::simple::LaplacianRecursiveGaussian for the procedural interface
20255
itk::LaplacianRecursiveGaussianImageFilter for the Doxygen on the original ITK class.
20259
C++ includes: sitkLaplacianRecursiveGaussianImageFilter.h
20262
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::Execute "
20264
Execute the filter on the input image
20268
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::Execute "
20270
Execute the filter on the input image with the given parameters
20274
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::GetName "
20280
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::GetNormalizeAcrossScale "
20282
Define which normalization factor will be used for the Gaussian
20284
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
20289
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::GetSigma "
20291
Set Sigma value. Sigma is measured in the units of image spacing.
20295
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::LaplacianRecursiveGaussianImageFilter "
20297
Default Constructor that takes no arguments and initializes default
20302
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::NormalizeAcrossScaleOff "
20305
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::NormalizeAcrossScaleOn "
20307
Set the value of NormalizeAcrossScale to true or false respectfully.
20311
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::SetNormalizeAcrossScale "
20313
Define which normalization factor will be used for the Gaussian
20315
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
20320
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::SetSigma "
20322
Set Sigma value. Sigma is measured in the units of image spacing.
20326
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::ToString "
20328
Print ourselves out
20332
%feature("docstring") itk::simple::LaplacianRecursiveGaussianImageFilter::~LaplacianRecursiveGaussianImageFilter "
20339
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter "
20341
Segments structures in images based on a second derivative image
20346
The SegmentationLevelSetImageFilter class and the LaplacianSegmentationLevelSetFunction class contain additional information necessary to the full
20347
understanding of how to use this filter.
20349
This class is a level set method segmentation filter. It constructs a
20350
speed function which is zero at image edges as detected by a Laplacian
20351
filter. The evolving level set front will therefore tend to lock onto
20352
zero crossings in the image. The level set front moves fastest near
20355
The Laplacian segmentation filter is intended primarily as a tool for
20356
refining existing segmentations. The initial isosurface (as given in
20357
the seed input image) should ideally be very close to the segmentation
20358
boundary of interest. The idea is that a rough segmentation can be
20359
refined by allowing the isosurface to deform slightly to achieve a
20360
better fit to the edge features of an image. One example of such an
20361
application is to refine the output of a hand segmented image.
20363
Because values in the Laplacian feature image will tend to be low
20364
except near edge features, this filter is not effective for segmenting
20365
large image regions from small seed surfaces.
20367
This filter requires two inputs. The first input is a seed image. This
20368
seed image must contain an isosurface that you want to use as the seed
20369
for your segmentation. It can be a binary, graylevel, or floating
20370
point image. The only requirement is that it contain a closed
20371
isosurface that you will identify as the seed by setting the
20372
IsosurfaceValue parameter of the filter. For a binary image you will
20373
want to set your isosurface value halfway between your on and off
20374
values (i.e. for 0's and 1's, use an isosurface value of 0.5).
20376
The second input is the feature image. This is the image from which
20377
the speed function will be calculated. For most applications, this is
20378
the image that you want to segment. The desired isosurface in your
20379
seed image should lie within the region of your feature image that you
20380
are trying to segment.
20381
Note that this filter does no preprocessing of the feature image
20382
before thresholding. Because second derivative calculations are highly
20383
sensitive to noise, isotropic or anisotropic smoothing of the feature
20384
image can dramatically improve the results.
20387
See SegmentationLevelSetImageFilter for more information on Inputs.
20389
The filter outputs a single, scalar, real-valued image. Positive
20390
*values in the output image are inside the segmentated region and
20391
negative *values in the image are outside of the inside region. The
20392
zero crossings of *the image correspond to the position of the level
20395
See SparseFieldLevelSetImageFilter and SegmentationLevelSetImageFilter for more information.
20397
This filter has no parameters other than those described in SegmentationLevelSetImageFilter .
20400
SegmentationLevelSetImageFilter
20402
LaplacianSegmentationLevelSetFunction ,
20404
SparseFieldLevelSetImageFilter
20406
itk::simple::LaplacianSegmentationLevelSet for the procedural interface
20408
itk::LaplacianSegmentationLevelSetImageFilter for the Doxygen on the original ITK class.
20411
C++ includes: sitkLaplacianSegmentationLevelSetImageFilter.h
20414
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::Execute "
20416
Execute the filter on the input images
20420
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::Execute "
20422
Execute the filter on the input images with the given parameters
20426
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetCurvatureScaling "
20429
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetElapsedIterations "
20431
Number of iterations run.
20434
This is a measurement. Its value is updated in the Execute methods, so
20435
the value will only be valid after an execution.
20439
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetMaximumRMSError "
20442
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetName "
20448
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetNumberOfIterations "
20451
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetPropagationScaling "
20454
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetReverseExpansionDirection "
20457
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::GetRMSChange "
20459
The Root Mean Square of the levelset upon termination.
20462
This is a measurement. Its value is updated in the Execute methods, so
20463
the value will only be valid after an execution.
20467
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::LaplacianSegmentationLevelSetImageFilter "
20469
Default Constructor that takes no arguments and initializes default
20474
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::ReverseExpansionDirectionOff "
20477
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::ReverseExpansionDirectionOn "
20479
Set the value of ReverseExpansionDirection to true or false
20484
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::SetCurvatureScaling "
20487
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::SetMaximumRMSError "
20490
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::SetNumberOfIterations "
20493
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::SetPropagationScaling "
20496
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::SetReverseExpansionDirection "
20499
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::ToString "
20501
Print ourselves out
20505
%feature("docstring") itk::simple::LaplacianSegmentationLevelSetImageFilter::~LaplacianSegmentationLevelSetImageFilter "
20512
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter "
20514
This filter sharpens an image using a Laplacian. LaplacianSharpening
20515
highlights regions of rapid intensity change and therefore highlights
20516
or enhances the edges. The result is an image that appears more in
20520
The LaplacianSharpening at each pixel location is computed by
20521
convolution with the itk::LaplacianOperator .
20523
The input to this filter is a scalar-valued itk::Image of arbitrary dimension. The output is a scalar-valued itk::Image .
20530
NeighborhoodOperator
20532
NeighborhoodIterator
20541
itk::simple::LaplacianSharpening for the procedural interface
20543
itk::LaplacianSharpeningImageFilter for the Doxygen on the original ITK class.
20547
C++ includes: sitkLaplacianSharpeningImageFilter.h
20550
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::Execute "
20552
Execute the filter on the input image
20556
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::Execute "
20558
Execute the filter on the input image with the given parameters
20562
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::GetName "
20568
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::GetUseImageSpacing "
20570
Set/Get whether or not the filter will use the spacing of the input
20571
image in its calculations
20575
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::LaplacianSharpeningImageFilter "
20577
Default Constructor that takes no arguments and initializes default
20582
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::SetUseImageSpacing "
20584
Set/Get whether or not the filter will use the spacing of the input
20585
image in its calculations
20589
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::ToString "
20591
Print ourselves out
20595
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::UseImageSpacingOff "
20598
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::UseImageSpacingOn "
20600
Set the value of UseImageSpacing to true or false respectfully.
20604
%feature("docstring") itk::simple::LaplacianSharpeningImageFilter::~LaplacianSharpeningImageFilter "
20611
%feature("docstring") itk::simple::LessEqualImageFilter "
20613
Implements pixel-wise generic operation of two images, or of an image
20617
This class is parameterized over the types of the two input images and
20618
the type of the output image. It is also parameterized by the
20619
operation to be applied. A Functor style is used.
20621
The constant must be of the same type than the pixel type of the
20622
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
20623
GetConstant() methods are provided as shortcuts to set or get the
20624
constant value without manipulating the decorator.
20628
UnaryFunctorImageFilter TernaryFunctorImageFilter
20633
Apply a predefined operation to corresponding pixels in two images
20635
Apply a custom operation to corresponding pixels in two images
20637
itk::simple::LessEqual for the procedural interface
20639
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
20643
C++ includes: sitkLessEqualImageFilter.h
20646
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20648
Execute the filter on the input images
20652
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20654
Execute the filter on the input images with the given parameters
20658
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20660
Execute the filter with an image and a constant
20664
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20667
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20669
Execute the filter on an image and a constant with the given
20674
%feature("docstring") itk::simple::LessEqualImageFilter::Execute "
20677
%feature("docstring") itk::simple::LessEqualImageFilter::GetBackgroundValue "
20679
Set/Get the value used to mark the false pixels of the operator.
20683
%feature("docstring") itk::simple::LessEqualImageFilter::GetForegroundValue "
20685
Set/Get the value used to mark the true pixels of the operator.
20689
%feature("docstring") itk::simple::LessEqualImageFilter::GetName "
20695
%feature("docstring") itk::simple::LessEqualImageFilter::LessEqualImageFilter "
20697
Default Constructor that takes no arguments and initializes default
20702
%feature("docstring") itk::simple::LessEqualImageFilter::SetBackgroundValue "
20704
Set/Get the value used to mark the false pixels of the operator.
20708
%feature("docstring") itk::simple::LessEqualImageFilter::SetForegroundValue "
20710
Set/Get the value used to mark the true pixels of the operator.
20714
%feature("docstring") itk::simple::LessEqualImageFilter::ToString "
20716
Print ourselves out
20720
%feature("docstring") itk::simple::LessEqualImageFilter::~LessEqualImageFilter "
20727
%feature("docstring") itk::simple::LessImageFilter "
20729
Implements pixel-wise generic operation of two images, or of an image
20733
This class is parameterized over the types of the two input images and
20734
the type of the output image. It is also parameterized by the
20735
operation to be applied. A Functor style is used.
20737
The constant must be of the same type than the pixel type of the
20738
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
20739
GetConstant() methods are provided as shortcuts to set or get the
20740
constant value without manipulating the decorator.
20744
UnaryFunctorImageFilter TernaryFunctorImageFilter
20749
Apply a predefined operation to corresponding pixels in two images
20751
Apply a custom operation to corresponding pixels in two images
20753
itk::simple::Less for the procedural interface
20755
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
20759
C++ includes: sitkLessImageFilter.h
20762
%feature("docstring") itk::simple::LessImageFilter::Execute "
20764
Execute the filter on the input images
20768
%feature("docstring") itk::simple::LessImageFilter::Execute "
20770
Execute the filter on the input images with the given parameters
20774
%feature("docstring") itk::simple::LessImageFilter::Execute "
20776
Execute the filter with an image and a constant
20780
%feature("docstring") itk::simple::LessImageFilter::Execute "
20783
%feature("docstring") itk::simple::LessImageFilter::Execute "
20785
Execute the filter on an image and a constant with the given
20790
%feature("docstring") itk::simple::LessImageFilter::Execute "
20793
%feature("docstring") itk::simple::LessImageFilter::GetBackgroundValue "
20795
Set/Get the value used to mark the false pixels of the operator.
20799
%feature("docstring") itk::simple::LessImageFilter::GetForegroundValue "
20801
Set/Get the value used to mark the true pixels of the operator.
20805
%feature("docstring") itk::simple::LessImageFilter::GetName "
20811
%feature("docstring") itk::simple::LessImageFilter::LessImageFilter "
20813
Default Constructor that takes no arguments and initializes default
20818
%feature("docstring") itk::simple::LessImageFilter::SetBackgroundValue "
20820
Set/Get the value used to mark the false pixels of the operator.
20824
%feature("docstring") itk::simple::LessImageFilter::SetForegroundValue "
20826
Set/Get the value used to mark the true pixels of the operator.
20830
%feature("docstring") itk::simple::LessImageFilter::ToString "
20832
Print ourselves out
20836
%feature("docstring") itk::simple::LessImageFilter::~LessImageFilter "
20843
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter "
20845
Deformably register two images using level set motion.
20848
LevelSetMotionFilter implements a deformable registration algorithm
20849
that aligns a fixed and a moving image under level set motion. The
20850
equations of motion are similar to those of the DemonsRegistrationFilter . The main differences are: (1) Gradients of the moving image are
20851
calculated on a smoothed image while intensity difference are measured
20852
on the original images (2) Magnitude of the motion vector is a
20853
function of the differences in intensity between the fixed and moving
20854
pixel. An adaptive timestep is calculated based on the maximum motion
20855
vector over the entire field to ensure stability. The timestep also
20856
implictly converts the motion vector measured in units of intensity to
20857
a vector measured in physical units. Demons, on the other hand,
20858
defines its motion vectors as function of both the intensity
20859
differences and gradient magnitude at each respective pixel. Consider
20860
two separate pixels with the same intensity differences between the
20861
corresponding fixed and moving pixel pairs. In demons, the motion
20862
vector of the pixel over a low gradient region will be larger than the
20863
motion vector of the pixel over a large gradient region. This leads to
20864
an unstable vector field. In the levelset approach, the motion vectors
20865
will be proportional to the gradients, scaled by the maximum gradient
20866
over the entire field. The pixel with at the lower gradient position
20867
will more less than the pixel at the higher gradient position. (3)
20868
Gradients are calculated using minmod finite difference instead of
20869
using central differences.
20871
A deformation field is represented as a image whose pixel type is some
20872
vector type with at least N elements, where N is the dimension of the
20873
fixed image. The vector type must support element access via operator
20874
[]. It is assumed that the vector elements behave like floating point
20877
This class is templated over the fixed image type, moving image type
20878
and the deformation field type.
20880
The input fixed and moving images are set via methods SetFixedImage
20881
and SetMovingImage respectively. An initial deformation field maybe
20882
set via SetInitialDisplacementField or SetInput. If no initial field
20883
is set, a zero field is used as the initial condition.
20885
The algorithm has one parameters: the number of iteration to be
20888
The output deformation field can be obtained via methods GetOutput or
20889
GetDisplacementField.
20891
This class make use of the finite difference solver hierarchy. Update
20892
for each iteration is computed in LevelSetMotionFunction.
20896
This filter assumes that the fixed image type, moving image type and
20897
deformation field type all have the same number of dimensions.
20898
Ref: B.C. Vemuri, J. Ye, Y. Chen, C.M. Leonard. \"Image registration
20899
via level-set motion: applications to atlas-based segmentation\".
20900
Medical Image Analysis. Vol. 7. pp. 1-20. 2003.
20904
LevelSetMotionRegistrationFunction
20906
DemonsRegistrationFilter
20908
itk::LevelSetMotionRegistrationFilter for the Doxygen on the original ITK class.
20911
C++ includes: sitkLevelSetMotionRegistrationFilter.h
20914
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::Execute "
20916
Execute the filter on the input image
20920
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::Execute "
20922
Execute the filter on the input image with the given parameters
20926
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetAlpha "
20929
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetElapsedIterations "
20931
Number of iterations run.
20934
This is a measurement. Its value is updated in the Execute methods, so
20935
the value will only be valid after an execution.
20939
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetGradientMagnitudeThreshold "
20942
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetGradientSmoothingStandardDeviations "
20945
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetIntensityDifferenceThreshold "
20948
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetMaximumError "
20950
Set/Get the desired maximum error of the Guassian kernel approximate.
20954
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetMaximumKernelWidth "
20956
Set/Get the desired limits of the Gaussian kernel width.
20960
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetMaximumRMSError "
20963
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetMetric "
20965
Get the metric value. The metric value is the mean square difference
20966
in intensity between the fixed image and transforming moving image
20967
computed over the the overlapping region between the two images. This
20968
is value is only available for the previous iteration and NOT the
20971
This is a measurement. Its value is updated in the Execute methods, so
20972
the value will only be valid after an execution.
20976
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetName "
20982
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetNumberOfIterations "
20985
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetRMSChange "
20987
The Root Mean Square of the levelset upon termination.
20990
This is a measurement. Its value is updated in the Execute methods, so
20991
the value will only be valid after an execution.
20995
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetSmoothDisplacementField "
20997
Set/Get whether the displacement field is smoothed (regularized).
20998
Smoothing the displacement yields a solution elastic in nature. If
20999
SmoothDisplacementField is on, then the displacement field is smoothed
21000
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
21004
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetSmoothUpdateField "
21006
Set/Get whether the update field is smoothed (regularized). Smoothing
21007
the update field yields a solution viscous in nature. If
21008
SmoothUpdateField is on, then the update field is smoothed with a
21009
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
21013
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetStandardDeviations "
21015
Set/Get the Gaussian smoothing standard deviations for the
21016
displacement field. The values are set with respect to pixel
21021
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetUpdateFieldStandardDeviations "
21023
Set the Gaussian smoothing standard deviations for the update field.
21024
The values are set with respect to pixel coordinates.
21028
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::GetUseImageSpacing "
21031
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::LevelSetMotionRegistrationFilter "
21033
Default Constructor that takes no arguments and initializes default
21038
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetAlpha "
21040
Set/Get the parameter alpha. Alpha is added to the calculated gradient
21041
magnitude prior to normalizing the gradient to protect against
21042
numerical instability as the gradient magnitude approaches zero. This
21043
should be set as a small fraction of the intensity dynamic range, for
21044
instance 0.04%. Default is the absolute (not percentage) value of 0.1.
21048
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetGradientMagnitudeThreshold "
21050
Set/Get the threshold below which the gradient magnitude is considered
21051
the zero vector. Default is 1e-9.
21055
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetGradientSmoothingStandardDeviations "
21057
Set/Get the standard deviation used for smoothing the moving image
21058
prior to calculating gradients. The standard deviation is measured in
21059
physical units (for instance mm). Note that this smoothing value is
21060
not to be confused with the
21061
PDEDeformableRegistrationFilter::SetStandardDeviations() method. The
21062
method in PDEDeformableRegistrationFilter is for setting the smoothing parameters for regularizing the
21063
deformation field between interations. Those smoothing parameters are
21064
set in pixel units not physical units. Deformation field smoothing is
21065
not done by default in LevelSetMotionRegistration. This smoothing
21066
parameter is to condition the gradient calculation and parameter is
21067
specified in physical units.
21071
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetIntensityDifferenceThreshold "
21073
Set/Get the threshold below which the absolute difference of intensity
21074
yields a match. When the intensities match between a moving and fixed
21075
image pixel, the update vector (for that iteration) will be the zero
21076
vector. Default is 0.001.
21080
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetMaximumError "
21082
Set/Get the desired maximum error of the Guassian kernel approximate.
21086
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetMaximumKernelWidth "
21088
Set/Get the desired limits of the Gaussian kernel width.
21092
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetMaximumRMSError "
21095
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetNumberOfIterations "
21098
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetSmoothDisplacementField "
21100
Set/Get whether the displacement field is smoothed (regularized).
21101
Smoothing the displacement yields a solution elastic in nature. If
21102
SmoothDisplacementField is on, then the displacement field is smoothed
21103
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
21107
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetSmoothUpdateField "
21109
Set/Get whether the update field is smoothed (regularized). Smoothing
21110
the update field yields a solution viscous in nature. If
21111
SmoothUpdateField is on, then the update field is smoothed with a
21112
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
21116
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetStandardDeviations "
21118
Set/Get the Gaussian smoothing standard deviations for the
21119
displacement field. The values are set with respect to pixel
21124
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetStandardDeviations "
21126
Set the values of the StandardDeviations vector all to value
21130
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetUpdateFieldStandardDeviations "
21132
Set the Gaussian smoothing standard deviations for the update field.
21133
The values are set with respect to pixel coordinates.
21137
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetUpdateFieldStandardDeviations "
21139
Set the values of the UpdateFieldStandardDeviations vector all to
21144
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SetUseImageSpacing "
21147
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SmoothDisplacementFieldOff "
21150
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SmoothDisplacementFieldOn "
21152
Set the value of SmoothDisplacementField to true or false
21157
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SmoothUpdateFieldOff "
21160
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::SmoothUpdateFieldOn "
21162
Set the value of SmoothUpdateField to true or false respectfully.
21166
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::ToString "
21168
Print ourselves out
21172
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::UseImageSpacingOff "
21175
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::UseImageSpacingOn "
21177
Set the value of UseImageSpacing to true or false respectfully.
21181
%feature("docstring") itk::simple::LevelSetMotionRegistrationFilter::~LevelSetMotionRegistrationFilter "
21188
%feature("docstring") itk::simple::LiThresholdImageFilter "
21190
Threshold an image using the Li Threshold.
21193
This filter creates a binary thresholded image that separates an image
21194
into foreground and background components. The filter computes the
21195
threshold using the LiThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
21198
Richard Beare. Department of Medicine, Monash University, Melbourne,
21200
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
21201
de Jouy-en-Josas, France.
21203
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
21207
HistogramThresholdImageFilter
21209
itk::simple::LiThreshold for the procedural interface
21211
itk::LiThresholdImageFilter for the Doxygen on the original ITK class.
21214
C++ includes: sitkLiThresholdImageFilter.h
21217
%feature("docstring") itk::simple::LiThresholdImageFilter::Execute "
21219
Execute the filter on the input image
21223
%feature("docstring") itk::simple::LiThresholdImageFilter::Execute "
21226
%feature("docstring") itk::simple::LiThresholdImageFilter::Execute "
21228
Execute the filter on the input image with the given parameters
21232
%feature("docstring") itk::simple::LiThresholdImageFilter::Execute "
21235
%feature("docstring") itk::simple::LiThresholdImageFilter::GetInsideValue "
21237
Get the \"inside\" pixel value.
21241
%feature("docstring") itk::simple::LiThresholdImageFilter::GetMaskOutput "
21244
%feature("docstring") itk::simple::LiThresholdImageFilter::GetMaskValue "
21247
%feature("docstring") itk::simple::LiThresholdImageFilter::GetName "
21253
%feature("docstring") itk::simple::LiThresholdImageFilter::GetNumberOfHistogramBins "
21256
%feature("docstring") itk::simple::LiThresholdImageFilter::GetOutsideValue "
21258
Get the \"outside\" pixel value.
21262
%feature("docstring") itk::simple::LiThresholdImageFilter::GetThreshold "
21264
Get the computed threshold.
21267
This is a measurement. Its value is updated in the Execute methods, so
21268
the value will only be valid after an execution.
21272
%feature("docstring") itk::simple::LiThresholdImageFilter::LiThresholdImageFilter "
21274
Default Constructor that takes no arguments and initializes default
21279
%feature("docstring") itk::simple::LiThresholdImageFilter::MaskOutputOff "
21282
%feature("docstring") itk::simple::LiThresholdImageFilter::MaskOutputOn "
21284
Set the value of MaskOutput to true or false respectfully.
21288
%feature("docstring") itk::simple::LiThresholdImageFilter::SetInsideValue "
21290
Set the \"inside\" pixel value.
21294
%feature("docstring") itk::simple::LiThresholdImageFilter::SetMaskOutput "
21296
Do you want the output to be masked by the mask used in histogram
21297
construction. Only relevant if masking is in use.
21301
%feature("docstring") itk::simple::LiThresholdImageFilter::SetMaskValue "
21303
The value in the mask image, if used, indicating voxels that should be
21304
included. Default is the max of pixel type, as in the
21305
MaskedImageToHistogramFilter
21309
%feature("docstring") itk::simple::LiThresholdImageFilter::SetNumberOfHistogramBins "
21311
Set/Get the number of histogram bins.
21315
%feature("docstring") itk::simple::LiThresholdImageFilter::SetOutsideValue "
21317
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
21321
%feature("docstring") itk::simple::LiThresholdImageFilter::ToString "
21323
Print ourselves out
21327
%feature("docstring") itk::simple::LiThresholdImageFilter::~LiThresholdImageFilter "
21334
%feature("docstring") itk::simple::Log10ImageFilter "
21336
Computes the log10 of each pixel.
21339
The computation is performed using std::log10(x).
21341
itk::simple::Log10 for the procedural interface
21343
itk::Log10ImageFilter for the Doxygen on the original ITK class.
21346
C++ includes: sitkLog10ImageFilter.h
21349
%feature("docstring") itk::simple::Log10ImageFilter::Execute "
21351
Execute the filter on the input image
21355
%feature("docstring") itk::simple::Log10ImageFilter::GetName "
21361
%feature("docstring") itk::simple::Log10ImageFilter::Log10ImageFilter "
21363
Default Constructor that takes no arguments and initializes default
21368
%feature("docstring") itk::simple::Log10ImageFilter::ToString "
21370
Print ourselves out
21374
%feature("docstring") itk::simple::Log10ImageFilter::~Log10ImageFilter "
21381
%feature("docstring") itk::simple::LogImageFilter "
21383
Computes the log() of each pixel.
21388
itk::simple::Log for the procedural interface
21390
itk::LogImageFilter for the Doxygen on the original ITK class.
21393
C++ includes: sitkLogImageFilter.h
21396
%feature("docstring") itk::simple::LogImageFilter::Execute "
21398
Execute the filter on the input image
21402
%feature("docstring") itk::simple::LogImageFilter::GetName "
21408
%feature("docstring") itk::simple::LogImageFilter::LogImageFilter "
21410
Default Constructor that takes no arguments and initializes default
21415
%feature("docstring") itk::simple::LogImageFilter::ToString "
21417
Print ourselves out
21421
%feature("docstring") itk::simple::LogImageFilter::~LogImageFilter "
21428
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter "
21430
Implements pixel-wise conversion of magnitude and phase data into
21434
This filter is parametrized over the types of the two input images and
21435
the type of the output image.
21437
The filter expect all images to have the same dimension (e.g. all 2D,
21438
or all 3D, or all ND)
21440
itk::simple::MagnitudeAndPhaseToComplex for the procedural interface
21442
itk::MagnitudeAndPhaseToComplexImageFilter for the Doxygen on the original ITK class.
21445
C++ includes: sitkMagnitudeAndPhaseToComplexImageFilter.h
21448
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::Execute "
21450
Execute the filter on the input images
21454
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::Execute "
21456
Execute the filter with an image and a constant
21460
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::Execute "
21463
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::GetName "
21469
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::MagnitudeAndPhaseToComplexImageFilter "
21471
Default Constructor that takes no arguments and initializes default
21476
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::ToString "
21478
Print ourselves out
21482
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplexImageFilter::~MagnitudeAndPhaseToComplexImageFilter "
21489
%feature("docstring") itk::simple::MaskImageFilter "
21491
Mask an image with a mask.
21494
This class is templated over the types of the input image type, the
21495
mask image type and the type of the output image. Numeric conversions
21496
(castings) are done by the C++ defaults.
21498
The pixel type of the input 2 image must have a valid definition of
21499
the operator != with zero. This condition is required because
21500
internally this filter will perform the operation
21503
The pixel from the input 1 is cast to the pixel type of the output
21506
Note that the input and the mask images must be of the same size.
21510
Any pixel value other than masking value (0 by default) will not be
21514
MaskNegatedImageFilter
21519
Apply a mask to an image
21521
itk::simple::Mask for the procedural interface
21523
itk::MaskImageFilter for the Doxygen on the original ITK class.
21527
C++ includes: sitkMaskImageFilter.h
21530
%feature("docstring") itk::simple::MaskImageFilter::Execute "
21532
Execute the filter on the input image
21536
%feature("docstring") itk::simple::MaskImageFilter::Execute "
21538
Execute the filter on the input image with the given parameters
21542
%feature("docstring") itk::simple::MaskImageFilter::GetName "
21548
%feature("docstring") itk::simple::MaskImageFilter::GetOutsideValue "
21551
%feature("docstring") itk::simple::MaskImageFilter::MaskImageFilter "
21553
Default Constructor that takes no arguments and initializes default
21558
%feature("docstring") itk::simple::MaskImageFilter::SetOutsideValue "
21560
Method to explicitly set the outside value of the mask. Defaults to 0
21564
%feature("docstring") itk::simple::MaskImageFilter::ToString "
21566
Print ourselves out
21570
%feature("docstring") itk::simple::MaskImageFilter::~MaskImageFilter "
21577
%feature("docstring") itk::simple::MaskNegatedImageFilter "
21579
Mask an image with the negative of a mask.
21582
This class is templated over the types of the input image type, the
21583
mask image type and the type of the output image. Numeric conversions
21584
(castings) are done by the C++ defaults. The pixel type of the input 2
21585
image must have a valid definition of the operator != with zero. This
21586
condition is required because internally this filter will perform the
21587
operation ifpixel_from_mask_image!=0pixel_output_image=output_valueels
21588
epixel_output_image=pixel_input_image The pixel from the input 1 is
21589
cast to the pixel type of the output image. Note that the input and
21590
the mask images must be of the same size.
21592
Any pixel value other than 0 will not be masked out.
21600
Apply the inverse of a mask to an image
21603
itk::simple::MaskNegated for the procedural interface
21605
itk::MaskNegatedImageFilter for the Doxygen on the original ITK class.
21608
C++ includes: sitkMaskNegatedImageFilter.h
21611
%feature("docstring") itk::simple::MaskNegatedImageFilter::Execute "
21613
Execute the filter on the input image
21617
%feature("docstring") itk::simple::MaskNegatedImageFilter::GetName "
21623
%feature("docstring") itk::simple::MaskNegatedImageFilter::MaskNegatedImageFilter "
21625
Default Constructor that takes no arguments and initializes default
21630
%feature("docstring") itk::simple::MaskNegatedImageFilter::ToString "
21632
Print ourselves out
21636
%feature("docstring") itk::simple::MaskNegatedImageFilter::~MaskNegatedImageFilter "
21643
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter "
21645
Calculate masked normalized cross correlation using FFTs.
21648
This filter calculates the masked normalized cross correlation (NCC)
21649
of two images under masks using FFTs instead of spatial correlation.
21650
It is much faster than spatial correlation for reasonably large
21651
structuring elements. This filter is not equivalent to simply masking
21652
the images first and then correlating them; the latter approach yields
21653
incorrect results because the zeros in the images still affect the
21654
metric in the correlation process. This filter implements the masked
21655
NCC correctly so that the masked-out regions are completely ignored.
21656
The fundamental difference is described in detail in the references
21657
below. If the masks are set to images of all ones, the result of this
21658
filter is the same as standard NCC.
21660
Inputs: Two images are required as inputs, fixedImage and movingImage,
21661
and two are optional, fixedMask and movingMask. In the context of
21662
correlation, inputs are often defined as: \"image\" and \"template\".
21663
In this filter, the fixedImage plays the role of the image, and the
21664
movingImage plays the role of the template. However, this filter is
21665
capable of correlating any two images and is not restricted to small
21666
movingImages (templates). In the fixedMask and movingMask, non-zero
21667
positive values indicate locations of useful information in the
21668
corresponding image, whereas zero and negative values indicate
21669
locations that should be masked out (ignored). Internally, the masks
21670
are converted to have values of only 0 and 1. For each optional mask
21671
that is not set, the filter internally creates an image of ones, which
21672
is equivalent to not masking the image. Thus, if both masks are not
21673
set, the result will be equivalent to unmasked NCC. For example, if
21674
only a mask for the fixed image is needed, the movingMask can either
21675
not be set or can be set to an image of ones.
21677
Optional parameters: The RequiredNumberOfOverlappingPixels enables the
21678
user to specify the minimum number of voxels of the two masks that
21679
must overlap; any location in the correlation map that results from
21680
fewer than this number of voxels will be set to zero. Larger values
21681
zero-out pixels on a larger border around the correlation image. Thus,
21682
larger values remove less stable computations but also limit the
21683
capture range. If RequiredNumberOfOverlappingPixels is set to 0, the
21684
default, no zeroing will take place.
21686
The RequiredFractionOfOverlappingPixels enables the user to specify a
21687
fraction of the maximum number of overlapping pixels that need to
21688
overlap; any location in the correlation map that results from fewer
21689
than the product of this fraction and the internally computed maximum
21690
number of overlapping pixels will be set to zero. The value ranges
21691
between 0.0 and 1.0. This is very useful when the user does does not
21692
know beforehand the maximum number of pixels of the masks that will
21693
overlap. For example, when the masks have strange shapes, it is
21694
difficult to predict how the correlation of the masks will interact
21695
and what the maximum overlap will be. It is also useful when the mask
21696
shapes or sizes change because it is relative to the internally
21697
computed maximum of the overlap. Larger values zero-out pixels on a
21698
larger border around the correlation image. Thus, larger values remove
21699
less stable computations but also limit the capture range. Experiments
21700
have shown that a value between 0.1 and 0.6 works well for images with
21701
significant overlap and between 0.05 and 0.1 for images with little
21702
overlap (such as in stitching applications). If
21703
RequiredFractionOfOverlappingPixels is set to 0, the default, no
21704
zeroing will take place.
21706
The user can either specify RequiredNumberOfOverlappingPixels or
21707
RequiredFractionOfOverlappingPixels (or both or none). Internally, the
21708
number of required pixels resulting from both of these methods is
21709
calculated and the one that gives the largest number of pixels is
21710
chosen. Since these both default to 0, if a user only sets one, the
21713
Image size: fixedImage and movingImage need not be the same size, but
21714
fixedMask must be the same size as fixedImage, and movingMask must be
21715
the same size as movingImage. Furthermore, whereas some algorithms
21716
require that the \"template\" be smaller than the \"image\" because of
21717
errors in the regions where the two are not fully overlapping, this
21718
filter has no such restriction.
21720
Image spacing: Since the computations are done in the pixel domain, all
21721
input images must have the same spacing.
21723
Outputs; The output is an image of RealPixelType that is the masked
21724
NCC of the two images and its values range from -1.0 to 1.0. The size
21725
of this NCC image is, by definition, size(fixedImage) +
21726
size(movingImage) - 1.
21728
Example filter usage:
21732
The pixel type of the output image must be of real type (float or
21733
double). ConceptChecking is used to enforce the output pixel type. You
21734
will get a compilation error if the pixel type of the output image is
21735
not float or double.
21736
References: 1) D. Padfield. \"Masked object registration in the
21737
Fourier domain.\" Transactions on Image Processing. 2) D. Padfield. \"Masked FFT registration\". In Proc.
21738
Computer Vision and Pattern Recognition, 2010.
21741
: Dirk Padfield, GE Global Research, padfield@research.ge.com
21744
itk::simple::MaskedFFTNormalizedCorrelation for the procedural interface
21746
itk::MaskedFFTNormalizedCorrelationImageFilter for the Doxygen on the original ITK class.
21749
C++ includes: sitkMaskedFFTNormalizedCorrelationImageFilter.h
21752
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::Execute "
21754
Execute the filter on the input image
21758
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::Execute "
21760
Execute the filter on the input image with the given parameters
21764
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::GetName "
21770
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::GetRequiredFractionOfOverlappingPixels "
21772
Set and get the required fraction of overlapping pixels
21776
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::GetRequiredNumberOfOverlappingPixels "
21778
Set and get the required number of overlapping pixels
21782
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::MaskedFFTNormalizedCorrelationImageFilter "
21784
Default Constructor that takes no arguments and initializes default
21789
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::SetRequiredFractionOfOverlappingPixels "
21791
Set and get the required fraction of overlapping pixels
21795
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::SetRequiredNumberOfOverlappingPixels "
21797
Set and get the required number of overlapping pixels
21801
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::ToString "
21803
Print ourselves out
21807
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelationImageFilter::~MaskedFFTNormalizedCorrelationImageFilter "
21814
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter "
21816
Threshold an image using the MaximumEntropy Threshold.
21819
This filter creates a binary thresholded image that separates an image
21820
into foreground and background components. The filter computes the
21821
threshold using the MaximumEntropyThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
21824
Richard Beare. Department of Medicine, Monash University, Melbourne,
21826
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
21827
de Jouy-en-Josas, France.
21829
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
21833
HistogramThresholdImageFilter
21835
itk::simple::MaximumEntropyThreshold for the procedural interface
21837
itk::MaximumEntropyThresholdImageFilter for the Doxygen on the original ITK class.
21840
C++ includes: sitkMaximumEntropyThresholdImageFilter.h
21843
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::Execute "
21845
Execute the filter on the input image
21849
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::Execute "
21852
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::Execute "
21854
Execute the filter on the input image with the given parameters
21858
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::Execute "
21861
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetInsideValue "
21863
Get the \"inside\" pixel value.
21867
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetMaskOutput "
21870
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetMaskValue "
21873
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetName "
21879
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetNumberOfHistogramBins "
21882
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetOutsideValue "
21884
Get the \"outside\" pixel value.
21888
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::GetThreshold "
21890
Get the computed threshold.
21893
This is a measurement. Its value is updated in the Execute methods, so
21894
the value will only be valid after an execution.
21898
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::MaskOutputOff "
21901
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::MaskOutputOn "
21903
Set the value of MaskOutput to true or false respectfully.
21907
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::MaximumEntropyThresholdImageFilter "
21909
Default Constructor that takes no arguments and initializes default
21914
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::SetInsideValue "
21916
Set the \"inside\" pixel value.
21920
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::SetMaskOutput "
21922
Do you want the output to be masked by the mask used in histogram
21923
construction. Only relevant if masking is in use.
21927
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::SetMaskValue "
21929
The value in the mask image, if used, indicating voxels that should be
21930
included. Default is the max of pixel type, as in the
21931
MaskedImageToHistogramFilter
21935
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::SetNumberOfHistogramBins "
21937
Set/Get the number of histogram bins.
21941
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::SetOutsideValue "
21943
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
21947
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::ToString "
21949
Print ourselves out
21953
%feature("docstring") itk::simple::MaximumEntropyThresholdImageFilter::~MaximumEntropyThresholdImageFilter "
21960
%feature("docstring") itk::simple::MaximumImageFilter "
21962
Implements a pixel-wise operator Max(a,b) between two images.
21965
The pixel values of the output image are the maximum between the
21966
corresponding pixels of the two input images.
21968
This class is templated over the types of the two input images and the
21969
type of the output image. Numeric conversions (castings) are done by
21976
Pixel wise compare two input images and set the output pixel to their
21979
itk::simple::Maximum for the procedural interface
21981
itk::MaximumImageFilter for the Doxygen on the original ITK class.
21985
C++ includes: sitkMaximumImageFilter.h
21988
%feature("docstring") itk::simple::MaximumImageFilter::Execute "
21990
Execute the filter on the input images
21994
%feature("docstring") itk::simple::MaximumImageFilter::Execute "
21996
Execute the filter with an image and a constant
22000
%feature("docstring") itk::simple::MaximumImageFilter::Execute "
22003
%feature("docstring") itk::simple::MaximumImageFilter::GetName "
22009
%feature("docstring") itk::simple::MaximumImageFilter::MaximumImageFilter "
22011
Default Constructor that takes no arguments and initializes default
22016
%feature("docstring") itk::simple::MaximumImageFilter::ToString "
22018
Print ourselves out
22022
%feature("docstring") itk::simple::MaximumImageFilter::~MaximumImageFilter "
22029
%feature("docstring") itk::simple::MaximumProjectionImageFilter "
22031
Maximum projection.
22034
This class was contributed to the insight journal by Gaetan Lehmann.
22035
The original paper can be found at https://hdl.handle.net/1926/164
22038
Gaetan Lehmann. Biologie du Developpement et de la reproduction, inra
22039
de jouy-en-josas, France.
22042
ProjectionImageFilter
22044
MedianProjectionImageFilter
22046
MeanProjectionImageFilter
22048
MinimumProjectionImageFilter
22050
StandardDeviationProjectionImageFilter
22052
SumProjectionImageFilter
22054
BinaryProjectionImageFilter
22056
itk::simple::MaximumProjection for the procedural interface
22058
itk::MaximumProjectionImageFilter for the Doxygen on the original ITK class.
22061
C++ includes: sitkMaximumProjectionImageFilter.h
22064
%feature("docstring") itk::simple::MaximumProjectionImageFilter::Execute "
22066
Execute the filter on the input image
22070
%feature("docstring") itk::simple::MaximumProjectionImageFilter::Execute "
22072
Execute the filter on the input image with the given parameters
22076
%feature("docstring") itk::simple::MaximumProjectionImageFilter::GetName "
22082
%feature("docstring") itk::simple::MaximumProjectionImageFilter::GetProjectionDimension "
22085
%feature("docstring") itk::simple::MaximumProjectionImageFilter::MaximumProjectionImageFilter "
22087
Default Constructor that takes no arguments and initializes default
22092
%feature("docstring") itk::simple::MaximumProjectionImageFilter::SetProjectionDimension "
22095
%feature("docstring") itk::simple::MaximumProjectionImageFilter::ToString "
22097
Print ourselves out
22101
%feature("docstring") itk::simple::MaximumProjectionImageFilter::~MaximumProjectionImageFilter "
22108
%feature("docstring") itk::simple::MeanImageFilter "
22110
Applies an averaging filter to an image.
22113
Computes an image where a given pixel is the mean value of the the
22114
pixels in a neighborhood about the corresponding input pixel.
22116
A mean filter is one of the family of linear filters.
22124
NeighborhoodOperator
22126
NeighborhoodIterator
22131
Mean filter an image
22133
itk::simple::Mean for the procedural interface
22135
itk::MeanImageFilter for the Doxygen on the original ITK class.
22139
C++ includes: sitkMeanImageFilter.h
22142
%feature("docstring") itk::simple::MeanImageFilter::Execute "
22144
Execute the filter on the input image
22148
%feature("docstring") itk::simple::MeanImageFilter::Execute "
22150
Execute the filter on the input image with the given parameters
22154
%feature("docstring") itk::simple::MeanImageFilter::GetName "
22160
%feature("docstring") itk::simple::MeanImageFilter::GetRadius "
22163
%feature("docstring") itk::simple::MeanImageFilter::MeanImageFilter "
22165
Default Constructor that takes no arguments and initializes default
22170
%feature("docstring") itk::simple::MeanImageFilter::SetRadius "
22173
%feature("docstring") itk::simple::MeanImageFilter::SetRadius "
22175
Set the values of the Radius vector all to value
22179
%feature("docstring") itk::simple::MeanImageFilter::ToString "
22181
Print ourselves out
22185
%feature("docstring") itk::simple::MeanImageFilter::~MeanImageFilter "
22192
%feature("docstring") itk::simple::MeanProjectionImageFilter "
22197
This class was contributed to the Insight Journal by Gaetan Lehmann.
22198
The original paper can be found at https://hdl.handle.net/1926/164
22201
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
22202
de Jouy-en-Josas, France.
22205
ProjectionImageFilter
22207
MedianProjectionImageFilter
22209
MinimumProjectionImageFilter
22211
StandardDeviationProjectionImageFilter
22213
SumProjectionImageFilter
22215
BinaryProjectionImageFilter
22217
MaximumProjectionImageFilter
22219
itk::simple::MeanProjection for the procedural interface
22221
itk::MeanProjectionImageFilter for the Doxygen on the original ITK class.
22224
C++ includes: sitkMeanProjectionImageFilter.h
22227
%feature("docstring") itk::simple::MeanProjectionImageFilter::Execute "
22229
Execute the filter on the input image
22233
%feature("docstring") itk::simple::MeanProjectionImageFilter::Execute "
22235
Execute the filter on the input image with the given parameters
22239
%feature("docstring") itk::simple::MeanProjectionImageFilter::GetName "
22245
%feature("docstring") itk::simple::MeanProjectionImageFilter::GetProjectionDimension "
22248
%feature("docstring") itk::simple::MeanProjectionImageFilter::MeanProjectionImageFilter "
22250
Default Constructor that takes no arguments and initializes default
22255
%feature("docstring") itk::simple::MeanProjectionImageFilter::SetProjectionDimension "
22258
%feature("docstring") itk::simple::MeanProjectionImageFilter::ToString "
22260
Print ourselves out
22264
%feature("docstring") itk::simple::MeanProjectionImageFilter::~MeanProjectionImageFilter "
22271
%feature("docstring") itk::simple::MedianImageFilter "
22273
Applies a median filter to an image.
22276
Computes an image where a given pixel is the median value of the the
22277
pixels in a neighborhood about the corresponding input pixel.
22279
A median filter is one of the family of nonlinear filters. It is used
22280
to smooth an image without being biased by outliers or shot noise.
22282
This filter requires that the input pixel type provides an operator<()
22283
(LessThan Comparable).
22291
NeighborhoodOperator
22293
NeighborhoodIterator
22298
Median filter an image
22300
Median filter an RGB image
22302
itk::simple::Median for the procedural interface
22304
itk::MedianImageFilter for the Doxygen on the original ITK class.
22308
C++ includes: sitkMedianImageFilter.h
22311
%feature("docstring") itk::simple::MedianImageFilter::Execute "
22313
Execute the filter on the input image
22317
%feature("docstring") itk::simple::MedianImageFilter::Execute "
22319
Execute the filter on the input image with the given parameters
22323
%feature("docstring") itk::simple::MedianImageFilter::GetName "
22329
%feature("docstring") itk::simple::MedianImageFilter::GetRadius "
22332
%feature("docstring") itk::simple::MedianImageFilter::MedianImageFilter "
22334
Default Constructor that takes no arguments and initializes default
22339
%feature("docstring") itk::simple::MedianImageFilter::SetRadius "
22342
%feature("docstring") itk::simple::MedianImageFilter::SetRadius "
22344
Set the values of the Radius vector all to value
22348
%feature("docstring") itk::simple::MedianImageFilter::ToString "
22350
Print ourselves out
22354
%feature("docstring") itk::simple::MedianImageFilter::~MedianImageFilter "
22361
%feature("docstring") itk::simple::MedianProjectionImageFilter "
22366
This class was contributed to the Insight Journal by Gaetan Lehmann.
22367
The original paper can be found at https://hdl.handle.net/1926/164
22370
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
22371
de Jouy-en-Josas, France.
22374
ProjectionImageFilter
22376
StandardDeviationProjectionImageFilter
22378
SumProjectionImageFilter
22380
BinaryProjectionImageFilter
22382
MaximumProjectionImageFilter
22384
MinimumProjectionImageFilter
22386
MeanProjectionImageFilter
22388
itk::simple::MedianProjection for the procedural interface
22390
itk::MedianProjectionImageFilter for the Doxygen on the original ITK class.
22393
C++ includes: sitkMedianProjectionImageFilter.h
22396
%feature("docstring") itk::simple::MedianProjectionImageFilter::Execute "
22398
Execute the filter on the input image
22402
%feature("docstring") itk::simple::MedianProjectionImageFilter::Execute "
22404
Execute the filter on the input image with the given parameters
22408
%feature("docstring") itk::simple::MedianProjectionImageFilter::GetName "
22414
%feature("docstring") itk::simple::MedianProjectionImageFilter::GetProjectionDimension "
22417
%feature("docstring") itk::simple::MedianProjectionImageFilter::MedianProjectionImageFilter "
22419
Default Constructor that takes no arguments and initializes default
22424
%feature("docstring") itk::simple::MedianProjectionImageFilter::SetProjectionDimension "
22427
%feature("docstring") itk::simple::MedianProjectionImageFilter::ToString "
22429
Print ourselves out
22433
%feature("docstring") itk::simple::MedianProjectionImageFilter::~MedianProjectionImageFilter "
22440
%feature("docstring") itk::simple::MergeLabelMapFilter "
22442
Merges several Label Maps.
22445
This filter takes one or more input Label Map and merges them.
22447
SetMethod() can be used to change how the filter manage the labels from the
22448
different label maps. KEEP (0): MergeLabelMapFilter do its best to keep the label unchanged, but if a label is already
22449
used in a previous label map, a new label is assigned. AGGREGATE (1):
22450
If the same label is found several times in the label maps, the label
22451
objects with the same label are merged. PACK (2): MergeLabelMapFilter relabel all the label objects by order of processing. No conflict can
22452
occur. STRICT (3): MergeLabelMapFilter keeps the labels unchanged and raises an exception if the same label
22453
is found in several images.
22455
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
22458
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
22459
de Jouy-en-Josas, France.
22462
ShapeLabelObject , RelabelComponentImageFilter
22464
itk::simple::MergeLabelMapFilter for the procedural interface
22467
C++ includes: sitkMergeLabelMapFilter.h
22470
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22472
Execute the filter on the input images
22476
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22479
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22482
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22485
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22488
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22491
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22493
Execute the filter on the input images with the given parameters
22497
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22500
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22503
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22506
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22509
%feature("docstring") itk::simple::MergeLabelMapFilter::Execute "
22512
%feature("docstring") itk::simple::MergeLabelMapFilter::GetMethod "
22514
Set/Get the method used to merge the label maps
22518
%feature("docstring") itk::simple::MergeLabelMapFilter::GetName "
22524
%feature("docstring") itk::simple::MergeLabelMapFilter::MergeLabelMapFilter "
22526
Default Constructor that takes no arguments and initializes default
22531
%feature("docstring") itk::simple::MergeLabelMapFilter::SetMethod "
22533
Set/Get the method used to merge the label maps
22537
%feature("docstring") itk::simple::MergeLabelMapFilter::ToString "
22539
Print ourselves out
22543
%feature("docstring") itk::simple::MergeLabelMapFilter::~MergeLabelMapFilter "
22550
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter "
22552
Denoise an image using min/max curvature flow.
22555
MinMaxCurvatureFlowImageFilter implements a curvature driven image denoising algorithm. Iso-
22556
brightness contours in the grayscale input image are viewed as a level
22557
set. The level set is then evolved using a curvature-based speed
22560
\\\\[ I_t = F_{\\\\mbox{minmax}} |\\\\nabla I| \\\\]
22562
where $ F_{\\\\mbox{minmax}} = \\\\max(\\\\kappa,0) $ if $ \\\\mbox{Avg}_{\\\\mbox{stencil}}(x) $ is less than or equal to $ T_{thresold} $ and $ \\\\min(\\\\kappa,0) $ , otherwise. $ \\\\kappa $ is the mean curvature of the iso-brightness contour at point $ x $ .
22564
In min/max curvature flow, movement is turned on or off depending on
22565
the scale of the noise one wants to remove. Switching depends on the
22566
average image value of a region of radius $ R $ around each point. The choice of $ R $ , the stencil radius, governs the scale of the noise to be removed.
22568
The threshold value $ T_{threshold} $ is the average intensity obtained in the direction perpendicular to
22569
the gradient at point $ x $ at the extrema of the local neighborhood.
22571
This filter make use of the multi-threaded finite difference solver
22572
hierarchy. Updates are computed using a MinMaxCurvatureFlowFunction object. A zero flux Neumann boundary condition is used when computing
22573
derivatives near the data boundary.
22577
This filter assumes that the input and output types have the same
22578
dimensions. This filter also requires that the output image pixels are
22579
of a real type. This filter works for any dimensional images, however
22580
for dimensions greater than 3D, an expensive brute-force search is
22581
used to compute the local threshold.
22582
Reference: \"Level Set Methods and Fast Marching Methods\", J.A.
22583
Sethian, Cambridge Press, Chapter 16, Second edition, 1999.
22587
MinMaxCurvatureFlowFunction
22589
CurvatureFlowImageFilter
22591
BinaryMinMaxCurvatureFlowImageFilter
22593
itk::simple::MinMaxCurvatureFlow for the procedural interface
22595
itk::MinMaxCurvatureFlowImageFilter for the Doxygen on the original ITK class.
22598
C++ includes: sitkMinMaxCurvatureFlowImageFilter.h
22601
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::Execute "
22603
Execute the filter on the input image
22607
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::Execute "
22609
Execute the filter on the input image with the given parameters
22613
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::GetName "
22619
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::GetNumberOfIterations "
22622
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::GetStencilRadius "
22624
Set/Get the stencil radius.
22628
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::GetTimeStep "
22631
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::MinMaxCurvatureFlowImageFilter "
22633
Default Constructor that takes no arguments and initializes default
22638
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::SetNumberOfIterations "
22641
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::SetStencilRadius "
22643
Set/Get the stencil radius.
22647
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::SetTimeStep "
22650
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::ToString "
22652
Print ourselves out
22656
%feature("docstring") itk::simple::MinMaxCurvatureFlowImageFilter::~MinMaxCurvatureFlowImageFilter "
22663
%feature("docstring") itk::simple::MinimumImageFilter "
22665
Implements a pixel-wise operator Min(a,b) between two images.
22668
The pixel values of the output image are the minimum between the
22669
corresponding pixels of the two input images.
22671
This class is templated over the types of the two input images and the
22672
type of the output image. Numeric conversions (castings) are done by
22679
Pixel wise compare two input images and set the output pixel to their
22682
itk::simple::Minimum for the procedural interface
22684
itk::MinimumImageFilter for the Doxygen on the original ITK class.
22688
C++ includes: sitkMinimumImageFilter.h
22691
%feature("docstring") itk::simple::MinimumImageFilter::Execute "
22693
Execute the filter on the input images
22697
%feature("docstring") itk::simple::MinimumImageFilter::Execute "
22699
Execute the filter with an image and a constant
22703
%feature("docstring") itk::simple::MinimumImageFilter::Execute "
22706
%feature("docstring") itk::simple::MinimumImageFilter::GetName "
22712
%feature("docstring") itk::simple::MinimumImageFilter::MinimumImageFilter "
22714
Default Constructor that takes no arguments and initializes default
22719
%feature("docstring") itk::simple::MinimumImageFilter::ToString "
22721
Print ourselves out
22725
%feature("docstring") itk::simple::MinimumImageFilter::~MinimumImageFilter "
22732
%feature("docstring") itk::simple::MinimumMaximumImageFilter "
22734
Computes the minimum and the maximum intensity values of an image.
22737
It is templated over input image type only. This filter just copies
22738
the input image through this output to be included within the
22739
pipeline. The implementation uses the StatisticsImageFilter .
22743
StatisticsImageFilter
22745
itk::MinimumMaximumImageFilter for the Doxygen on the original ITK class.
22748
C++ includes: sitkMinimumMaximumImageFilter.h
22751
%feature("docstring") itk::simple::MinimumMaximumImageFilter::Execute "
22753
Execute the filter on the input image
22757
%feature("docstring") itk::simple::MinimumMaximumImageFilter::GetMaximum "
22759
Return the computed Maximum.
22761
This is a measurement. Its value is updated in the Execute methods, so
22762
the value will only be valid after an execution.
22766
%feature("docstring") itk::simple::MinimumMaximumImageFilter::GetMinimum "
22768
Return the computed Minimum.
22770
This is a measurement. Its value is updated in the Execute methods, so
22771
the value will only be valid after an execution.
22775
%feature("docstring") itk::simple::MinimumMaximumImageFilter::GetName "
22781
%feature("docstring") itk::simple::MinimumMaximumImageFilter::MinimumMaximumImageFilter "
22783
Default Constructor that takes no arguments and initializes default
22788
%feature("docstring") itk::simple::MinimumMaximumImageFilter::ToString "
22790
Print ourselves out
22794
%feature("docstring") itk::simple::MinimumMaximumImageFilter::~MinimumMaximumImageFilter "
22801
%feature("docstring") itk::simple::MinimumProjectionImageFilter "
22803
Minimum projection.
22806
This class was contributed to the Insight Journal by Gaetan Lehmann.
22807
The original paper can be found at https://hdl.handle.net/1926/164
22810
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
22811
de Jouy-en-Josas, France.
22814
ProjectionImageFilter
22816
StandardDeviationProjectionImageFilter
22818
SumProjectionImageFilter
22820
BinaryProjectionImageFilter
22822
MaximumProjectionImageFilter
22824
MeanProjectionImageFilter
22826
itk::simple::MinimumProjection for the procedural interface
22828
itk::MinimumProjectionImageFilter for the Doxygen on the original ITK class.
22831
C++ includes: sitkMinimumProjectionImageFilter.h
22834
%feature("docstring") itk::simple::MinimumProjectionImageFilter::Execute "
22836
Execute the filter on the input image
22840
%feature("docstring") itk::simple::MinimumProjectionImageFilter::Execute "
22842
Execute the filter on the input image with the given parameters
22846
%feature("docstring") itk::simple::MinimumProjectionImageFilter::GetName "
22852
%feature("docstring") itk::simple::MinimumProjectionImageFilter::GetProjectionDimension "
22855
%feature("docstring") itk::simple::MinimumProjectionImageFilter::MinimumProjectionImageFilter "
22857
Default Constructor that takes no arguments and initializes default
22862
%feature("docstring") itk::simple::MinimumProjectionImageFilter::SetProjectionDimension "
22865
%feature("docstring") itk::simple::MinimumProjectionImageFilter::ToString "
22867
Print ourselves out
22871
%feature("docstring") itk::simple::MinimumProjectionImageFilter::~MinimumProjectionImageFilter "
22878
%feature("docstring") itk::simple::MirrorPadImageFilter "
22880
Increase the image size by padding with replicants of the input image
22884
MirrorPadImageFilter changes the image bounds of an image. Any added pixels are filled in
22885
with a mirrored replica of the input image. For instance, if the
22886
output image needs a pixel that is two pixels to the left of the
22887
LargestPossibleRegion of the input image, the value assigned will be
22888
from the pixel two pixels inside the left boundary of the
22889
LargestPossibleRegion. The image bounds of the output must be
22892
Visual explanation of padding regions. This filter is implemented as a
22893
multithreaded filter. It provides a ThreadedGenerateData() method for
22894
its implementation.
22898
WrapPadImageFilter , ConstantPadImageFilter
22903
Pad an image using mirroring over the boundaries
22905
itk::simple::MirrorPad for the procedural interface
22907
itk::MirrorPadImageFilter for the Doxygen on the original ITK class.
22911
C++ includes: sitkMirrorPadImageFilter.h
22914
%feature("docstring") itk::simple::MirrorPadImageFilter::Execute "
22916
Execute the filter on the input image
22920
%feature("docstring") itk::simple::MirrorPadImageFilter::Execute "
22922
Execute the filter on the input image with the given parameters
22926
%feature("docstring") itk::simple::MirrorPadImageFilter::GetName "
22932
%feature("docstring") itk::simple::MirrorPadImageFilter::GetPadLowerBound "
22935
%feature("docstring") itk::simple::MirrorPadImageFilter::GetPadUpperBound "
22938
%feature("docstring") itk::simple::MirrorPadImageFilter::MirrorPadImageFilter "
22940
Default Constructor that takes no arguments and initializes default
22945
%feature("docstring") itk::simple::MirrorPadImageFilter::SetPadLowerBound "
22948
%feature("docstring") itk::simple::MirrorPadImageFilter::SetPadUpperBound "
22951
%feature("docstring") itk::simple::MirrorPadImageFilter::ToString "
22953
Print ourselves out
22957
%feature("docstring") itk::simple::MirrorPadImageFilter::~MirrorPadImageFilter "
22964
%feature("docstring") itk::simple::ModulusImageFilter "
22966
Computes the modulus (x % dividend) pixel-wise.
22969
The input pixel type must support the c++ modulus operator (%).
22971
If the dividend is zero, the maximum value will be returned.
22974
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
22975
de Jouy-en-Josas, France.
22978
itk::simple::Modulus for the procedural interface
22980
itk::ModulusImageFilter for the Doxygen on the original ITK class.
22983
C++ includes: sitkModulusImageFilter.h
22986
%feature("docstring") itk::simple::ModulusImageFilter::Execute "
22988
Execute the filter on the input images
22992
%feature("docstring") itk::simple::ModulusImageFilter::Execute "
22994
Execute the filter with an image and a constant
22998
%feature("docstring") itk::simple::ModulusImageFilter::Execute "
23001
%feature("docstring") itk::simple::ModulusImageFilter::GetName "
23007
%feature("docstring") itk::simple::ModulusImageFilter::ModulusImageFilter "
23009
Default Constructor that takes no arguments and initializes default
23014
%feature("docstring") itk::simple::ModulusImageFilter::ToString "
23016
Print ourselves out
23020
%feature("docstring") itk::simple::ModulusImageFilter::~ModulusImageFilter "
23027
%feature("docstring") itk::simple::MomentsThresholdImageFilter "
23029
Threshold an image using the Moments Threshold.
23032
This filter creates a binary thresholded image that separates an image
23033
into foreground and background components. The filter computes the
23034
threshold using the MomentsThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
23037
Richard Beare. Department of Medicine, Monash University, Melbourne,
23039
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
23040
de Jouy-en-Josas, France.
23042
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
23046
HistogramThresholdImageFilter
23048
itk::simple::MomentsThreshold for the procedural interface
23050
itk::MomentsThresholdImageFilter for the Doxygen on the original ITK class.
23053
C++ includes: sitkMomentsThresholdImageFilter.h
23056
%feature("docstring") itk::simple::MomentsThresholdImageFilter::Execute "
23058
Execute the filter on the input image
23062
%feature("docstring") itk::simple::MomentsThresholdImageFilter::Execute "
23065
%feature("docstring") itk::simple::MomentsThresholdImageFilter::Execute "
23067
Execute the filter on the input image with the given parameters
23071
%feature("docstring") itk::simple::MomentsThresholdImageFilter::Execute "
23074
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetInsideValue "
23076
Get the \"inside\" pixel value.
23080
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetMaskOutput "
23083
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetMaskValue "
23086
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetName "
23092
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetNumberOfHistogramBins "
23095
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetOutsideValue "
23097
Get the \"outside\" pixel value.
23101
%feature("docstring") itk::simple::MomentsThresholdImageFilter::GetThreshold "
23103
Get the computed threshold.
23106
This is a measurement. Its value is updated in the Execute methods, so
23107
the value will only be valid after an execution.
23111
%feature("docstring") itk::simple::MomentsThresholdImageFilter::MaskOutputOff "
23114
%feature("docstring") itk::simple::MomentsThresholdImageFilter::MaskOutputOn "
23116
Set the value of MaskOutput to true or false respectfully.
23120
%feature("docstring") itk::simple::MomentsThresholdImageFilter::MomentsThresholdImageFilter "
23122
Default Constructor that takes no arguments and initializes default
23127
%feature("docstring") itk::simple::MomentsThresholdImageFilter::SetInsideValue "
23129
Set the \"inside\" pixel value.
23133
%feature("docstring") itk::simple::MomentsThresholdImageFilter::SetMaskOutput "
23135
Do you want the output to be masked by the mask used in histogram
23136
construction. Only relevant if masking is in use.
23140
%feature("docstring") itk::simple::MomentsThresholdImageFilter::SetMaskValue "
23142
The value in the mask image, if used, indicating voxels that should be
23143
included. Default is the max of pixel type, as in the
23144
MaskedImageToHistogramFilter
23148
%feature("docstring") itk::simple::MomentsThresholdImageFilter::SetNumberOfHistogramBins "
23150
Set/Get the number of histogram bins.
23154
%feature("docstring") itk::simple::MomentsThresholdImageFilter::SetOutsideValue "
23156
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
23160
%feature("docstring") itk::simple::MomentsThresholdImageFilter::ToString "
23162
Print ourselves out
23166
%feature("docstring") itk::simple::MomentsThresholdImageFilter::~MomentsThresholdImageFilter "
23173
%feature("docstring") itk::simple::MorphologicalGradientImageFilter "
23175
gray scale dilation of an image
23178
Dilate an image using grayscale morphology. Dilation takes the maximum
23179
of all the pixels identified by the structuring element.
23181
The structuring element is assumed to be composed of binary values
23182
(zero or one). Only elements of the structuring element having values
23183
> 0 are candidates for affecting the center pixel.
23187
MorphologyImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter
23189
itk::simple::MorphologicalGradient for the procedural interface
23191
itk::MorphologicalGradientImageFilter for the Doxygen on the original ITK class.
23194
C++ includes: sitkMorphologicalGradientImageFilter.h
23197
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::Execute "
23199
Execute the filter on the input image
23203
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::GetKernelRadius "
23206
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::GetKernelType "
23209
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::GetName "
23215
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::MorphologicalGradientImageFilter "
23217
Default Constructor that takes no arguments and initializes default
23222
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::SetKernelRadius "
23224
Kernel radius as a scale for isotropic structures
23228
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::SetKernelRadius "
23230
Set/Get the radius of the kernel structuring element as a vector.
23232
If the dimension of the image is greater then the length of r, then
23233
the radius will be padded. If it is less the r will be truncated.
23237
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::SetKernelType "
23239
Set/Get the kernel or structuring elemenent used for the morphology
23243
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::SetKernelType "
23246
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::ToString "
23248
Print ourselves out
23252
%feature("docstring") itk::simple::MorphologicalGradientImageFilter::~MorphologicalGradientImageFilter "
23259
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter "
23261
Morphological watershed transform from markers.
23264
The watershed transform is a tool for image segmentation that is fast
23265
and flexible and potentially fairly parameter free. It was originally
23266
derived from a geophysical model of rain falling on a terrain and a
23267
variety of more formal definitions have been devised to allow
23268
development of practical algorithms. If an image is considered as a
23269
terrain and divided into catchment basins then the hope is that each
23270
catchment basin would contain an object of interest.
23272
The output is a label image. A label image, sometimes referred to as a
23273
categorical image, has unique values for each region. For example, if
23274
a watershed produces 2 regions, all pixels belonging to one region
23275
would have value A, and all belonging to the other might have value B.
23276
Unassigned pixels, such as watershed lines, might have the background
23277
value (0 by convention).
23279
The simplest way of using the watershed is to preprocess the image we
23280
want to segment so that the boundaries of our objects are bright (e.g
23281
apply an edge detector) and compute the watershed transform of the
23282
edge image. Watershed lines will correspond to the boundaries and our
23283
problem will be solved. This is rarely useful in practice because
23284
there are always more regional minima than there are objects, either
23285
due to noise or natural variations in the object surfaces. Therefore,
23286
while many watershed lines do lie on significant boundaries, there are
23287
many that don't. Various methods can be used to reduce the number of
23288
minima in the image, like thresholding the smallest values, filtering
23289
the minima and/or smoothing the image.
23291
This filter use another approach to avoid the problem of over
23292
segmentation: it let the user provide a marker image which mark the
23293
minima in the input image and give them a label. The minima are
23294
imposed in the input image by the markers. The labels of the output
23295
image are the label of the marker image.
23297
The morphological watershed transform algorithm is described in
23298
Chapter 9.2 of Pierre Soille's book \"Morphological Image Analysis:
23299
Principles and Applications\", Second Edition, Springer, 2003.
23301
This code was contributed in the Insight Journal paper: \"The
23302
watershed transform in ITK - discussion and new developments\" by
23303
Beare R., Lehmann G. https://hdl.handle.net/1926/202 http://www.insight-journal.org/browse/publication/92
23306
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
23307
de Jouy-en-Josas, France.
23308
Richard Beare. Department of Medicine, Monash University, Melbourne,
23313
WatershedImageFilter , MorphologicalWatershedImageFilter
23315
itk::simple::MorphologicalWatershedFromMarkers for the procedural interface
23317
itk::MorphologicalWatershedFromMarkersImageFilter for the Doxygen on the original ITK class.
23320
C++ includes: sitkMorphologicalWatershedFromMarkersImageFilter.h
23323
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::Execute "
23325
Execute the filter on the input image
23329
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::Execute "
23331
Execute the filter on the input image with the given parameters
23335
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::FullyConnectedOff "
23338
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::FullyConnectedOn "
23340
Set the value of FullyConnected to true or false respectfully.
23344
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::GetFullyConnected "
23346
Set/Get whether the connected components are defined strictly by face
23347
connectivity or by face+edge+vertex connectivity. Default is
23348
FullyConnectedOff. For objects that are 1 pixel wide, use
23353
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::GetMarkWatershedLine "
23355
Set/Get whether the watershed pixel must be marked or not. Default is
23356
true. Set it to false do not only avoid writing watershed pixels, it
23357
also decrease algorithm complexity.
23361
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::GetName "
23367
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::MarkWatershedLineOff "
23370
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::MarkWatershedLineOn "
23372
Set the value of MarkWatershedLine to true or false respectfully.
23376
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::MorphologicalWatershedFromMarkersImageFilter "
23378
Default Constructor that takes no arguments and initializes default
23383
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::SetFullyConnected "
23385
Set/Get whether the connected components are defined strictly by face
23386
connectivity or by face+edge+vertex connectivity. Default is
23387
FullyConnectedOff. For objects that are 1 pixel wide, use
23392
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::SetMarkWatershedLine "
23394
Set/Get whether the watershed pixel must be marked or not. Default is
23395
true. Set it to false do not only avoid writing watershed pixels, it
23396
also decrease algorithm complexity.
23400
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::ToString "
23402
Print ourselves out
23406
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkersImageFilter::~MorphologicalWatershedFromMarkersImageFilter "
23413
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter "
23415
Watershed segmentation implementation with morphogical operators.
23418
Watershed pixel are labeled 0. TOutputImage should be an integer type.
23419
Labels of output image are in no particular order. You can reorder the
23420
labels such that object labels are consecutive and sorted based on
23421
object size by passing the output of this filter to a RelabelComponentImageFilter .
23423
The morphological watershed transform algorithm is described in
23424
Chapter 9.2 of Pierre Soille's book \"Morphological Image Analysis:
23425
Principles and Applications\", Second Edition, Springer, 2003.
23427
This code was contributed in the Insight Journal paper: \"The
23428
watershed transform in ITK - discussion and new developments\" by
23429
Beare R., Lehmann G. https://hdl.handle.net/1926/202 http://www.insight-journal.org/browse/publication/92
23432
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
23433
de Jouy-en-Josas, France.
23436
WatershedImageFilter , MorphologicalWatershedFromMarkersImageFilter
23438
itk::simple::MorphologicalWatershed for the procedural interface
23440
itk::MorphologicalWatershedImageFilter for the Doxygen on the original ITK class.
23443
C++ includes: sitkMorphologicalWatershedImageFilter.h
23446
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::Execute "
23448
Execute the filter on the input image
23452
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::Execute "
23454
Execute the filter on the input image with the given parameters
23458
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::FullyConnectedOff "
23461
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::FullyConnectedOn "
23463
Set the value of FullyConnected to true or false respectfully.
23467
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::GetFullyConnected "
23469
Set/Get whether the connected components are defined strictly by face
23470
connectivity or by face+edge+vertex connectivity. Default is
23471
FullyConnectedOff. For objects that are 1 pixel wide, use
23476
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::GetLevel "
23479
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::GetMarkWatershedLine "
23481
Set/Get whether the watershed pixel must be marked or not. Default is
23482
true. Set it to false do not only avoid writing watershed pixels, it
23483
also decrease algorithm complexity.
23487
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::GetName "
23493
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::MarkWatershedLineOff "
23496
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::MarkWatershedLineOn "
23498
Set the value of MarkWatershedLine to true or false respectfully.
23502
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::MorphologicalWatershedImageFilter "
23504
Default Constructor that takes no arguments and initializes default
23509
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::SetFullyConnected "
23511
Set/Get whether the connected components are defined strictly by face
23512
connectivity or by face+edge+vertex connectivity. Default is
23513
FullyConnectedOff. For objects that are 1 pixel wide, use
23518
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::SetLevel "
23521
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::SetMarkWatershedLine "
23523
Set/Get whether the watershed pixel must be marked or not. Default is
23524
true. Set it to false do not only avoid writing watershed pixels, it
23525
also decrease algorithm complexity.
23529
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::ToString "
23531
Print ourselves out
23535
%feature("docstring") itk::simple::MorphologicalWatershedImageFilter::~MorphologicalWatershedImageFilter "
23542
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter "
23544
This filter performs a pixelwise combination of an arbitrary number of
23545
input images, where each of them represents a segmentation of the same
23546
scene (i.e., image).
23549
The labelings in the images are weighted relative to each other based
23550
on their \"performance\" as estimated by an expectation-maximization
23551
algorithm. In the process, a ground truth segmentation is estimated,
23552
and the estimated performances of the individual segmentations are
23553
relative to this estimated ground truth.
23555
The algorithm is based on the binary STAPLE algorithm by Warfield et
23556
al. as published originally in
23558
S. Warfield, K. Zou, W. Wells, \"Validation of image segmentation and
23559
expert quality with an expectation-maximization algorithm\" in MICCAI
23560
2002: Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag,
23561
Heidelberg, Germany, 2002, pp. 298-306
23563
The multi-label algorithm implemented here is described in detail in
23565
T. Rohlfing, D. B. Russakoff, and C. R. Maurer, Jr., \"Performance-
23566
based classifier combination in atlas-based image segmentation using
23567
expectation-maximization parameter estimation,\" IEEE Transactions on
23568
Medical Imaging, vol. 23, pp. 983-994, Aug. 2004.
23571
All input volumes to this filter must be segmentations of an image,
23572
that is, they must have discrete pixel values where each value
23573
represents a different segmented object.
23574
Input volumes must all contain the same size RequestedRegions. Not all input images must contain all possible labels, but all label
23575
values must have the same meaning in all images.
23577
The filter can optionally be provided with estimates for the a priori
23578
class probabilities through the SetPriorProbabilities function. If no
23579
estimate is provided, one is automatically generated by analyzing the
23580
relative frequencies of the labels in the input images.
23583
The filter produces a single output volume. Each output pixel contains
23584
the label that has the highest probability of being the correct label,
23585
based on the performance models of the individual segmentations. If
23586
the maximum probaility is not unique, i.e., if more than one label
23587
have a maximum probability, then an \"undecided\" label is assigned to
23589
By default, the label used for undecided pixels is the maximum label
23590
value used in the input images plus one. Since it is possible for an
23591
image with 8 bit pixel values to use all 256 possible label values, it
23592
is permissible to combine 8 bit (i.e., byte) images into a 16 bit
23593
(i.e., short) output image.
23595
In addition to the combined image, the estimated confusion matrices
23596
for each of the input segmentations can be obtained through the
23597
GetConfusionMatrix member function.
23600
The label used for \"undecided\" labels can be set using
23601
SetLabelForUndecidedPixels. This functionality can be unset by calling
23602
UnsetLabelForUndecidedPixels.
23603
A termination threshold for the EM iteration can be defined by
23604
calling SetTerminationUpdateThreshold. The iteration terminates once
23605
no single parameter of any confusion matrix changes by less than this
23606
threshold. Alternatively, a maximum number of iterations can be
23607
specified by calling SetMaximumNumberOfIterations. The algorithm may
23608
still terminate after a smaller number of iterations if the
23609
termination threshold criterion is satisfied.
23612
This filter invokes IterationEvent() at each iteration of the E-M
23613
algorithm. Setting the AbortGenerateData() flag will cause the
23614
algorithm to halt after the current iteration and produce results just
23615
as if it had converged. The algorithm makes no attempt to report its
23616
progress since the number of iterations needed cannot be known in
23619
Torsten Rohlfing, SRI International, Neuroscience Program
23622
itk::simple::MultiLabelSTAPLE for the procedural interface
23625
C++ includes: sitkMultiLabelSTAPLEImageFilter.h
23628
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23630
Execute the filter on the input images
23634
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23637
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23640
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23643
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23646
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23649
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23651
Execute the filter on the input images with the given parameters
23655
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23658
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23661
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23664
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23667
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::Execute "
23670
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetConfusionMatrix "
23672
Get confusion matrix for the i-th input segmentation.
23674
This is an active measurement. It may be accessed while the filter is
23675
being executing in command call-backs and can be accessed after
23680
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetLabelForUndecidedPixels "
23682
Get label value used for undecided pixels.
23684
After updating the filter, this function returns the actual label
23685
value used for undecided pixels in the current output. Note that this
23686
value is overwritten when SetLabelForUndecidedPixels is called and the
23687
new value only becomes effective upon the next filter update.
23691
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetMaximumNumberOfIterations "
23693
Set maximum number of iterations.
23697
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetName "
23703
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetPriorProbabilities "
23705
Get prior class probabilities.
23707
After updating the filter, this function returns the actual prior
23708
class probabilities. If these were not previously set by a call to
23709
SetPriorProbabilities, then they are estimated from the input
23710
segmentations and the result is available through this function.
23714
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::GetTerminationUpdateThreshold "
23716
Set termination threshold based on confusion matrix parameter updates.
23720
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::MultiLabelSTAPLEImageFilter "
23722
Default Constructor that takes no arguments and initializes default
23727
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::SetLabelForUndecidedPixels "
23729
Set label value for undecided pixels.
23733
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::SetMaximumNumberOfIterations "
23735
Set maximum number of iterations.
23739
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::SetPriorProbabilities "
23741
Set manual estimates for the a priori class probabilities. The
23742
size of the array must be greater than the value of the largest label. The index into the array corresponds to the label
23743
value in the segmented image for the class.
23747
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::SetTerminationUpdateThreshold "
23749
Set termination threshold based on confusion matrix parameter updates.
23753
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::ToString "
23755
Print ourselves out
23759
%feature("docstring") itk::simple::MultiLabelSTAPLEImageFilter::~MultiLabelSTAPLEImageFilter "
23766
%feature("docstring") itk::simple::MultiplyImageFilter "
23768
Pixel-wise multiplication of two images.
23771
This class is templated over the types of the two input images and the
23772
type of the output image. Numeric conversions (castings) are done by
23779
Multiply two images together
23781
Multiply every pixel in an image by a constant
23783
itk::simple::Multiply for the procedural interface
23785
itk::MultiplyImageFilter for the Doxygen on the original ITK class.
23789
C++ includes: sitkMultiplyImageFilter.h
23792
%feature("docstring") itk::simple::MultiplyImageFilter::Execute "
23794
Execute the filter on the input images
23798
%feature("docstring") itk::simple::MultiplyImageFilter::Execute "
23800
Execute the filter with an image and a constant
23804
%feature("docstring") itk::simple::MultiplyImageFilter::Execute "
23807
%feature("docstring") itk::simple::MultiplyImageFilter::GetName "
23813
%feature("docstring") itk::simple::MultiplyImageFilter::MultiplyImageFilter "
23815
Default Constructor that takes no arguments and initializes default
23820
%feature("docstring") itk::simple::MultiplyImageFilter::ToString "
23822
Print ourselves out
23826
%feature("docstring") itk::simple::MultiplyImageFilter::~MultiplyImageFilter "
23833
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter "
23835
Implementation of the N4 bias field correction algorithm.
23838
The nonparametric nonuniform intensity normalization (N3) algorithm,
23839
as introduced by Sled et al. in 1998 is a method for correcting
23840
nonuniformity associated with MR images. The algorithm assumes a
23841
simple parametric model (Gaussian) for the bias field and does not
23842
require tissue class segmentation. In addition, there are only a
23843
couple of parameters to tune with the default values performing quite
23844
well. N3 has been publicly available as a set of perl scripts ( http://www.bic.mni.mcgill.ca/ServicesSoftwareAdvancedImageProcessingTo
23847
The N4 algorithm, encapsulated with this class, is a variation of the
23848
original N3 algorithm with the additional benefits of an improved
23849
B-spline fitting routine which allows for multiple resolutions to be
23850
used during the correction process. We also modify the iterative
23851
update component of algorithm such that the residual bias field is
23852
continually updated
23854
Notes for the user:
23855
Since much of the image manipulation is done in the log space of the
23856
intensities, input images with negative and small values (< 1) can
23857
produce poor results.
23859
The original authors recommend performing the bias field correction on
23860
a downsampled version of the original image.
23862
A binary mask or a weighted image can be supplied. If a binary mask is
23863
specified, those voxels in the input image which correspond to the
23864
voxels in the mask image are used to estimate the bias field. If a
23865
UseMaskLabel value is set to true, only voxels in the MaskImage that
23866
match the MaskLabel will be used; otherwise, all non-zero voxels in
23867
the MaskImage will be masked. If a confidence image is specified, the
23868
input voxels are weighted in the b-spline fitting routine according to
23869
the confidence voxel values.
23871
The filter returns the corrected image. If the bias field is wanted,
23872
one can reconstruct it using the class
23873
itkBSplineControlPointImageFilter. See the IJ article and the test
23874
file for an example.
23876
The 'Z' parameter in Sled's 1998 paper is the square root of the class
23877
variable 'm_WienerFilterNoise'.
23878
The basic algorithm iterates between sharpening the intensity
23879
histogram of the corrected input image and spatially smoothing those
23880
results with a B-spline scalar field estimate of the bias field.
23883
Nicholas J. Tustison
23884
Contributed by Nicholas J. Tustison, James C. Gee in the Insight
23885
Journal paper: https://hdl.handle.net/10380/3053
23888
J.G. Sled, A.P. Zijdenbos and A.C. Evans. \"A Nonparametric Method
23889
for Automatic Correction of Intensity Nonuniformity in Data\" IEEE
23890
Transactions on Medical Imaging, Vol 17, No 1. Feb 1998.
23892
N.J. Tustison, B.B. Avants, P.A. Cook, Y. Zheng, A. Egan, P.A.
23893
Yushkevich, and J.C. Gee. \"N4ITK: Improved N3 Bias Correction\" IEEE
23894
Transactions on Medical Imaging, 29(6):1310-1320, June 2010.
23896
itk::simple::N4BiasFieldCorrection for the procedural interface
23898
itk::N4BiasFieldCorrectionImageFilter for the Doxygen on the original ITK class.
23901
C++ includes: sitkN4BiasFieldCorrectionImageFilter.h
23904
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::Execute "
23906
Execute the filter on the input image
23910
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::Execute "
23912
Execute the filter on the input image with the given parameters
23916
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetBiasFieldFullWidthAtHalfMaximum "
23918
Get the full width at half maximum parameter characterizing the width
23919
of the Gaussian deconvolution. Default = 0.15.
23923
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetConvergenceThreshold "
23925
Get the convergence threshold. Convergence is determined by the
23926
coefficient of variation of the difference image between the current
23927
bias field estimate and the previous estimate. If this value is less
23928
than the specified threshold, the algorithm proceeds to the next
23929
fitting level or terminates if it is at the last level.
23933
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetMaximumNumberOfIterations "
23935
Get the maximum number of iterations specified at each fitting level.
23940
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetName "
23946
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetNumberOfControlPoints "
23948
Get the control point grid size defining the B-spline estimate of the
23949
scalar bias field. In each dimension, the B-spline mesh size is equal
23950
to the number of control points in that dimension minus the spline
23951
order. Default = 4 control points in each dimension for a mesh size of
23952
1 in each dimension.
23956
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetNumberOfHistogramBins "
23958
Get number of bins defining the log input intensity histogram. Default
23963
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetSplineOrder "
23965
Get the spline order defining the bias field estimate. Default = 3.
23969
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::GetWienerFilterNoise "
23971
Get the noise estimate defining the Wiener filter. Default = 0.01.
23975
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::N4BiasFieldCorrectionImageFilter "
23977
Default Constructor that takes no arguments and initializes default
23982
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetBiasFieldFullWidthAtHalfMaximum "
23984
Set the full width at half maximum parameter characterizing the width
23985
of the Gaussian deconvolution. Default = 0.15.
23989
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetConvergenceThreshold "
23991
Set the convergence threshold. Convergence is determined by the
23992
coefficient of variation of the difference image between the current
23993
bias field estimate and the previous estimate. If this value is less
23994
than the specified threshold, the algorithm proceeds to the next
23995
fitting level or terminates if it is at the last level.
23999
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetMaximumNumberOfIterations "
24001
Set the maximum number of iterations specified at each fitting level.
24006
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetNumberOfControlPoints "
24008
Set the control point grid size defining the B-spline estimate of the
24009
scalar bias field. In each dimension, the B-spline mesh size is equal
24010
to the number of control points in that dimension minus the spline
24011
order. Default = 4 control points in each dimension for a mesh size of
24012
1 in each dimension.
24016
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetNumberOfControlPoints "
24018
Set the values of the NumberOfControlPoints vector all to value
24022
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetNumberOfHistogramBins "
24024
Set number of bins defining the log input intensity histogram. Default
24029
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetSplineOrder "
24031
Set the spline order defining the bias field estimate. Default = 3.
24035
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::SetWienerFilterNoise "
24037
Set the noise estimate defining the Wiener filter. Default = 0.01.
24041
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::ToString "
24043
Print ourselves out
24047
%feature("docstring") itk::simple::N4BiasFieldCorrectionImageFilter::~N4BiasFieldCorrectionImageFilter "
24054
%feature("docstring") itk::simple::NaryAddImageFilter "
24056
Pixel-wise addition of N images.
24059
This class is templated over the types of the input images and the
24060
type of the output image. Numeric conversions (castings) are done by
24063
The pixel type of the input images must have a valid definition of the
24064
operator+ with each other. This condition is required because
24065
internally this filter will perform the operation
24068
Additionally the type resulting from the sum, will be cast to the
24069
pixel type of the output image.
24071
The total operation over one pixel will be
24074
For example, this filter could be used directly for adding images
24075
whose pixels are vectors of the same dimension, and to store the
24076
resulting vector in an output image of vector pixels.
24080
No numeric overflow checking is performed in this filter.
24083
itk::simple::NaryAdd for the procedural interface
24086
C++ includes: sitkNaryAddImageFilter.h
24089
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24091
Execute the filter on the input images
24095
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24098
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24101
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24104
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24107
%feature("docstring") itk::simple::NaryAddImageFilter::Execute "
24110
%feature("docstring") itk::simple::NaryAddImageFilter::GetName "
24116
%feature("docstring") itk::simple::NaryAddImageFilter::NaryAddImageFilter "
24118
Default Constructor that takes no arguments and initializes default
24123
%feature("docstring") itk::simple::NaryAddImageFilter::ToString "
24125
Print ourselves out
24129
%feature("docstring") itk::simple::NaryAddImageFilter::~NaryAddImageFilter "
24136
%feature("docstring") itk::simple::NaryMaximumImageFilter "
24138
Computes the pixel-wise maximum of several images.
24141
This class is templated over the types of the input images and the
24142
type of the output image. Numeric conversions (castings) are done by
24145
The pixel type of the output images must have a valid definition of
24146
the operator<. This condition is required because internally this
24147
filter will perform an operation similar to:
24149
(where current_maximum is also of type OutputPixelType)
24151
for each of the n input images.
24153
For example, this filter could be used directly to find a \"maximum
24154
projection\" of a series of images, often used in preliminary analysis
24155
of time-series data.
24159
This filter was contributed by Zachary Pincus from the Department of
24160
Biochemistry and Program in Biomedical Informatics at Stanford
24161
University School of Medicine
24165
itk::simple::NaryMaximum for the procedural interface
24168
C++ includes: sitkNaryMaximumImageFilter.h
24171
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24173
Execute the filter on the input images
24177
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24180
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24183
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24186
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24189
%feature("docstring") itk::simple::NaryMaximumImageFilter::Execute "
24192
%feature("docstring") itk::simple::NaryMaximumImageFilter::GetName "
24198
%feature("docstring") itk::simple::NaryMaximumImageFilter::NaryMaximumImageFilter "
24200
Default Constructor that takes no arguments and initializes default
24205
%feature("docstring") itk::simple::NaryMaximumImageFilter::ToString "
24207
Print ourselves out
24211
%feature("docstring") itk::simple::NaryMaximumImageFilter::~NaryMaximumImageFilter "
24218
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter "
24220
Label pixels that are connected to a seed and lie within a
24224
NeighborhoodConnectedImageFilter labels pixels with ReplaceValue that are connected to an initial Seed
24225
AND whose neighbors all lie within a Lower and Upper threshold range.
24227
itk::simple::NeighborhoodConnected for the procedural interface
24229
itk::NeighborhoodConnectedImageFilter for the Doxygen on the original ITK class.
24232
C++ includes: sitkNeighborhoodConnectedImageFilter.h
24235
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::AddSeed "
24237
AddSeed - Add a seed to the end of the list
24241
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::ClearSeeds "
24243
ClearSeeds - Clear out all seeds in the list
24247
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::Execute "
24249
Execute the filter on the input image
24253
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::Execute "
24255
Execute the filter on the input image with the given parameters
24259
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetLower "
24261
Set/Get the lower threshold. The default is 0.
24265
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetName "
24271
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetRadius "
24273
Get the radius of the neighborhood used to compute the median
24277
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetReplaceValue "
24279
Set/Get value to replace thresholded pixels. Pixels that lie * within
24280
Lower and Upper (inclusive) will be replaced with this value. The
24285
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetSeedList "
24291
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::GetUpper "
24293
Set/Get the upper threshold. The default is the largest possible value
24294
for the InputPixelType.
24298
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::NeighborhoodConnectedImageFilter "
24300
Default Constructor that takes no arguments and initializes default
24305
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetLower "
24307
Set/Get the lower threshold. The default is 0.
24311
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetRadius "
24313
Set the radius of the neighborhood used for a mask.
24317
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetRadius "
24319
Set the values of the Radius vector all to value
24323
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetReplaceValue "
24325
Set/Get value to replace thresholded pixels. Pixels that lie * within
24326
Lower and Upper (inclusive) will be replaced with this value. The
24331
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetSeed "
24333
SetSeed - Set list to a single seed
24337
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetSeedList "
24343
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::SetUpper "
24345
Set/Get the upper threshold. The default is the largest possible value
24346
for the InputPixelType.
24350
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::ToString "
24352
Print ourselves out
24356
%feature("docstring") itk::simple::NeighborhoodConnectedImageFilter::~NeighborhoodConnectedImageFilter "
24363
%feature("docstring") itk::simple::NoiseImageFilter "
24365
Calculate the local noise in an image.
24368
Computes an image where a given pixel is the standard deviation of the
24369
pixels in a neighborhood about the corresponding input pixel. This
24370
serves as an estimate of the local noise (or texture) in an image.
24371
Currently, this noise estimate assume a piecewise constant image. This
24372
filter should be extended to fitting a (hyper) plane to the
24373
neighborhood and calculating the standard deviation of the residuals
24374
to this (hyper) plane.
24382
NeighborhoodOperator
24384
NeighborhoodIterator
24389
Compute the local noise in an image
24391
itk::simple::Noise for the procedural interface
24393
itk::NoiseImageFilter for the Doxygen on the original ITK class.
24397
C++ includes: sitkNoiseImageFilter.h
24400
%feature("docstring") itk::simple::NoiseImageFilter::Execute "
24402
Execute the filter on the input image
24406
%feature("docstring") itk::simple::NoiseImageFilter::Execute "
24408
Execute the filter on the input image with the given parameters
24412
%feature("docstring") itk::simple::NoiseImageFilter::GetName "
24418
%feature("docstring") itk::simple::NoiseImageFilter::GetRadius "
24421
%feature("docstring") itk::simple::NoiseImageFilter::NoiseImageFilter "
24423
Default Constructor that takes no arguments and initializes default
24428
%feature("docstring") itk::simple::NoiseImageFilter::SetRadius "
24431
%feature("docstring") itk::simple::NoiseImageFilter::SetRadius "
24433
Set the values of the Radius vector all to value
24437
%feature("docstring") itk::simple::NoiseImageFilter::ToString "
24439
Print ourselves out
24443
%feature("docstring") itk::simple::NoiseImageFilter::~NoiseImageFilter "
24450
%feature("docstring") itk::simple::NonCopyable "
24452
An inheratable class to disable copying of a class.
24455
This class disable the implicit implementations of the assignment and
24456
copy constructor for derived classes. The instantiation of the default
24457
implementation for either method in a derived class will result in a
24458
compile-time error because they are private in this class. However,
24459
this policy is not absolute for derived classes because explicit
24460
implementation of these methods could be implemented.
24462
An advatange this apporach has is the class heiarchy makes it obvious
24463
what the intent is, as compared to other appoaches.
24465
For example you should not be able to copy singleton object, because
24466
there should only be one of them. To utilize this class just derive
24469
C++ includes: sitkNonCopyable.h
24473
%feature("docstring") itk::simple::NormalizeImageFilter "
24475
Normalize an image by setting its mean to zero and variance to one.
24478
NormalizeImageFilter shifts and scales an image so that the pixels in the image have a
24479
zero mean and unit variance. This filter uses StatisticsImageFilter to compute the mean and variance of the input and then applies ShiftScaleImageFilter to shift and scale the pixels.
24481
NB: since this filter normalizes the data to lie within -1 to 1,
24482
integral types will produce an image that DOES NOT HAVE a unit
24487
NormalizeToConstantImageFilter
24494
itk::simple::Normalize for the procedural interface
24496
itk::NormalizeImageFilter for the Doxygen on the original ITK class.
24500
C++ includes: sitkNormalizeImageFilter.h
24503
%feature("docstring") itk::simple::NormalizeImageFilter::Execute "
24505
Execute the filter on the input image
24509
%feature("docstring") itk::simple::NormalizeImageFilter::GetName "
24515
%feature("docstring") itk::simple::NormalizeImageFilter::NormalizeImageFilter "
24517
Default Constructor that takes no arguments and initializes default
24522
%feature("docstring") itk::simple::NormalizeImageFilter::ToString "
24524
Print ourselves out
24528
%feature("docstring") itk::simple::NormalizeImageFilter::~NormalizeImageFilter "
24535
%feature("docstring") itk::simple::NormalizeToConstantImageFilter "
24537
Scales image pixel intensities to make the sum of all pixels equal a
24538
user-defined constant.
24541
The default value of the constant is 1. It can be changed with SetConstant() .
24543
This transform is especially useful for normalizing a convolution
24546
This code was contributed in the Insight Journal paper: \"FFT based
24547
convolution\" by Lehmann G. https://hdl.handle.net/10380/3154
24550
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
24551
de Jouy-en-Josas, France.
24554
NormalizeImageFilter
24556
StatisticsImageFilter
24563
Scale all pixels so that their sum is a specified constant
24565
itk::simple::NormalizeToConstant for the procedural interface
24567
itk::NormalizeToConstantImageFilter for the Doxygen on the original ITK class.
24571
C++ includes: sitkNormalizeToConstantImageFilter.h
24574
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::Execute "
24576
Execute the filter on the input image
24580
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::Execute "
24582
Execute the filter on the input image with the given parameters
24586
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::GetConstant "
24588
Set/get the normalization constant.
24592
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::GetName "
24598
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::NormalizeToConstantImageFilter "
24600
Default Constructor that takes no arguments and initializes default
24605
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::SetConstant "
24607
Set/get the normalization constant.
24611
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::ToString "
24613
Print ourselves out
24617
%feature("docstring") itk::simple::NormalizeToConstantImageFilter::~NormalizeToConstantImageFilter "
24624
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter "
24626
Computes the normalized correlation of an image and a template.
24629
This filter calculates the normalized correlation between an image and
24630
the template. Normalized correlation is frequently use in feature
24631
detection because it is invariant to local changes in contrast.
24633
The filter can be given a mask. When presented with an input image and
24634
a mask, the normalized correlation is only calculated at those pixels
24643
NeighborhoodOperator
24645
NeighborhoodIterator
24650
Normalized correlation
24652
itk::simple::NormalizedCorrelation for the procedural interface
24654
itk::NormalizedCorrelationImageFilter for the Doxygen on the original ITK class.
24658
C++ includes: sitkNormalizedCorrelationImageFilter.h
24661
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter::Execute "
24663
Execute the filter on the input image
24667
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter::GetName "
24673
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter::NormalizedCorrelationImageFilter "
24675
Default Constructor that takes no arguments and initializes default
24680
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter::ToString "
24682
Print ourselves out
24686
%feature("docstring") itk::simple::NormalizedCorrelationImageFilter::~NormalizedCorrelationImageFilter "
24693
%feature("docstring") itk::simple::NotEqualImageFilter "
24695
Implements pixel-wise generic operation of two images, or of an image
24699
This class is parameterized over the types of the two input images and
24700
the type of the output image. It is also parameterized by the
24701
operation to be applied. A Functor style is used.
24703
The constant must be of the same type than the pixel type of the
24704
corresponding image. It is wrapped in a SimpleDataObjectDecorator so it can be updated through the pipeline. The SetConstant() and
24705
GetConstant() methods are provided as shortcuts to set or get the
24706
constant value without manipulating the decorator.
24710
UnaryFunctorImageFilter TernaryFunctorImageFilter
24715
Apply a predefined operation to corresponding pixels in two images
24717
Apply a custom operation to corresponding pixels in two images
24719
itk::simple::NotEqual for the procedural interface
24721
itk::BinaryFunctorImageFilter for the Doxygen on the original ITK class.
24725
C++ includes: sitkNotEqualImageFilter.h
24728
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24730
Execute the filter on the input images
24734
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24736
Execute the filter on the input images with the given parameters
24740
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24742
Execute the filter with an image and a constant
24746
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24749
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24751
Execute the filter on an image and a constant with the given
24756
%feature("docstring") itk::simple::NotEqualImageFilter::Execute "
24759
%feature("docstring") itk::simple::NotEqualImageFilter::GetBackgroundValue "
24761
Set/Get the value used to mark the false pixels of the operator.
24765
%feature("docstring") itk::simple::NotEqualImageFilter::GetForegroundValue "
24767
Set/Get the value used to mark the true pixels of the operator.
24771
%feature("docstring") itk::simple::NotEqualImageFilter::GetName "
24777
%feature("docstring") itk::simple::NotEqualImageFilter::NotEqualImageFilter "
24779
Default Constructor that takes no arguments and initializes default
24784
%feature("docstring") itk::simple::NotEqualImageFilter::SetBackgroundValue "
24786
Set/Get the value used to mark the false pixels of the operator.
24790
%feature("docstring") itk::simple::NotEqualImageFilter::SetForegroundValue "
24792
Set/Get the value used to mark the true pixels of the operator.
24796
%feature("docstring") itk::simple::NotEqualImageFilter::ToString "
24798
Print ourselves out
24802
%feature("docstring") itk::simple::NotEqualImageFilter::~NotEqualImageFilter "
24809
%feature("docstring") itk::simple::NotImageFilter "
24811
Implements the NOT logical operator pixel-wise on an image.
24814
This class is templated over the type of an input image and the type
24815
of the output image. Numeric conversions (castings) are done by the
24818
Since the logical NOT operation operates only on boolean types, the
24819
input type must be implicitly convertible to bool, which is only
24820
defined in C++ for integer types, the images passed to this filter
24821
must comply with the requirement of using integer pixel type.
24823
The total operation over one pixel will be
24826
Where \"!\" is the unary Logical NOT operator in C++.
24828
itk::simple::Not for the procedural interface
24830
itk::NotImageFilter for the Doxygen on the original ITK class.
24833
C++ includes: sitkNotImageFilter.h
24836
%feature("docstring") itk::simple::NotImageFilter::Execute "
24838
Execute the filter on the input image
24842
%feature("docstring") itk::simple::NotImageFilter::GetName "
24848
%feature("docstring") itk::simple::NotImageFilter::NotImageFilter "
24850
Default Constructor that takes no arguments and initializes default
24855
%feature("docstring") itk::simple::NotImageFilter::ToString "
24857
Print ourselves out
24861
%feature("docstring") itk::simple::NotImageFilter::~NotImageFilter "
24868
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter "
24870
Opening by reconstruction of an image.
24873
This filter preserves regions, in the foreground, that can completely
24874
contain the structuring element. At the same time, this filter
24875
eliminates all other regions of foreground pixels. Contrary to the
24876
mophological opening, the opening by reconstruction preserves the
24877
shape of the components that are not removed by erosion. The opening
24878
by reconstruction of an image \"f\" is defined as:
24880
OpeningByReconstruction(f) = DilationByRecontruction(f, Erosion(f)).
24882
Opening by reconstruction not only removes structures destroyed by the
24883
erosion, but also levels down the contrast of the brightest regions.
24884
If PreserveIntensities is on, a subsequent reconstruction by dilation
24885
using a marker image that is the original image for all unaffected
24888
Opening by reconstruction is described in Chapter 6.3.9 of Pierre
24889
Soille's book \"Morphological Image Analysis: Principles and
24890
Applications\", Second Edition, Springer, 2003.
24893
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
24894
de Jouy-en-Josas, France.
24897
GrayscaleMorphologicalOpeningImageFilter
24899
itk::simple::OpeningByReconstruction for the procedural interface
24901
itk::OpeningByReconstructionImageFilter for the Doxygen on the original ITK class.
24904
C++ includes: sitkOpeningByReconstructionImageFilter.h
24907
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::Execute "
24909
Execute the filter on the input image
24913
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::Execute "
24915
Execute the filter on the input image with the given parameters
24919
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::FullyConnectedOff "
24922
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::FullyConnectedOn "
24924
Set the value of FullyConnected to true or false respectfully.
24928
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::GetFullyConnected "
24930
Set/Get whether the connected components are defined strictly by face
24931
connectivity or by face+edge+vertex connectivity. Default is
24932
FullyConnectedOff. For objects that are 1 pixel wide, use
24937
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::GetKernelRadius "
24940
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::GetKernelType "
24943
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::GetName "
24949
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::GetPreserveIntensities "
24951
Set/Get whether the original intensities of the image retained for
24952
those pixels unaffected by the opening by reconstrcution. If Off, the
24953
output pixel contrast will be reduced.
24957
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::OpeningByReconstructionImageFilter "
24959
Default Constructor that takes no arguments and initializes default
24964
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::PreserveIntensitiesOff "
24967
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::PreserveIntensitiesOn "
24969
Set the value of PreserveIntensities to true or false respectfully.
24973
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetFullyConnected "
24975
Set/Get whether the connected components are defined strictly by face
24976
connectivity or by face+edge+vertex connectivity. Default is
24977
FullyConnectedOff. For objects that are 1 pixel wide, use
24982
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetKernelRadius "
24984
Kernel radius as a scale for isotropic structures
24988
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetKernelRadius "
24990
Set/Get the radius of the kernel structuring element as a vector.
24992
If the dimension of the image is greater then the length of r, then
24993
the radius will be padded. If it is less the r will be truncated.
24997
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetKernelType "
24999
Set/Get the kernel or structuring elemenent used for the morphology
25003
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetKernelType "
25006
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::SetPreserveIntensities "
25008
Set/Get whether the original intensities of the image retained for
25009
those pixels unaffected by the opening by reconstrcution. If Off, the
25010
output pixel contrast will be reduced.
25014
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::ToString "
25016
Print ourselves out
25020
%feature("docstring") itk::simple::OpeningByReconstructionImageFilter::~OpeningByReconstructionImageFilter "
25027
%feature("docstring") itk::simple::OrImageFilter "
25029
Implements the OR bitwise operator pixel-wise between two images.
25032
This class is templated over the types of the two input images and the
25033
type of the output image. Numeric conversions (castings) are done by
25036
Since the bitwise OR operation is only defined in C++ for integer
25037
types, the images passed to this filter must comply with the
25038
requirement of using integer pixel type.
25040
The total operation over one pixel will be
25043
Where \"|\" is the boolean OR operator in C++.
25049
Binary OR two images
25051
itk::simple::Or for the procedural interface
25053
itk::OrImageFilter for the Doxygen on the original ITK class.
25057
C++ includes: sitkOrImageFilter.h
25060
%feature("docstring") itk::simple::OrImageFilter::Execute "
25062
Execute the filter on the input images
25066
%feature("docstring") itk::simple::OrImageFilter::Execute "
25068
Execute the filter with an image and a constant
25072
%feature("docstring") itk::simple::OrImageFilter::Execute "
25075
%feature("docstring") itk::simple::OrImageFilter::GetName "
25081
%feature("docstring") itk::simple::OrImageFilter::OrImageFilter "
25083
Default Constructor that takes no arguments and initializes default
25088
%feature("docstring") itk::simple::OrImageFilter::ToString "
25090
Print ourselves out
25094
%feature("docstring") itk::simple::OrImageFilter::~OrImageFilter "
25101
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter "
25103
Threshold an image using multiple Otsu Thresholds.
25106
This filter creates a labeled image that separates the input image
25107
into various classes. The filter computes the thresholds using the OtsuMultipleThresholdsCalculator and applies those thresholds to the input image using the ThresholdLabelerImageFilter . The NumberOfHistogramBins and NumberOfThresholds can be set for the
25108
Calculator. The LabelOffset can be set for the ThresholdLabelerImageFilter .
25110
This filter also includes an option to use the valley emphasis
25111
algorithm from H.F. Ng, \"Automatic thresholding for defect
25112
detection\", Pattern Recognition Letters, (27): 1644-1649, 2006. The
25113
valley emphasis algorithm is particularly effective when the object to
25114
be thresholded is small. See the following tests for examples:
25115
itkOtsuMultipleThresholdsImageFilterTest3 and
25116
itkOtsuMultipleThresholdsImageFilterTest4 To use this algorithm,
25117
simple call the setter: SetValleyEmphasis(true) It is turned off by
25122
ScalarImageToHistogramGenerator
25124
OtsuMultipleThresholdsCalculator
25126
ThresholdLabelerImageFilter
25128
itk::simple::OtsuMultipleThresholds for the procedural interface
25130
itk::OtsuMultipleThresholdsImageFilter for the Doxygen on the original ITK class.
25133
C++ includes: sitkOtsuMultipleThresholdsImageFilter.h
25136
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::Execute "
25138
Execute the filter on the input image
25142
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::Execute "
25144
Execute the filter on the input image with the given parameters
25148
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetLabelOffset "
25150
Set/Get the offset which labels have to start from. Default is 0.
25154
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetName "
25160
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetNumberOfHistogramBins "
25162
Set/Get the number of histogram bins. Default is 128.
25166
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetNumberOfThresholds "
25168
Set/Get the number of thresholds. Default is 1.
25172
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetThresholds "
25174
Get the computed threshold.
25176
This is a measurement. Its value is updated in the Execute methods, so
25177
the value will only be valid after an execution.
25181
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::GetValleyEmphasis "
25183
Set/Get the use of valley emphasis. Default is false.
25187
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::OtsuMultipleThresholdsImageFilter "
25189
Default Constructor that takes no arguments and initializes default
25194
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::SetLabelOffset "
25196
Set/Get the offset which labels have to start from. Default is 0.
25200
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::SetNumberOfHistogramBins "
25202
Set/Get the number of histogram bins. Default is 128.
25206
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::SetNumberOfThresholds "
25208
Set/Get the number of thresholds. Default is 1.
25212
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::SetValleyEmphasis "
25214
Set/Get the use of valley emphasis. Default is false.
25218
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::ToString "
25220
Print ourselves out
25224
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::ValleyEmphasisOff "
25227
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::ValleyEmphasisOn "
25229
Set the value of ValleyEmphasis to true or false respectfully.
25233
%feature("docstring") itk::simple::OtsuMultipleThresholdsImageFilter::~OtsuMultipleThresholdsImageFilter "
25240
%feature("docstring") itk::simple::OtsuThresholdImageFilter "
25242
Threshold an image using the Otsu Threshold.
25245
This filter creates a binary thresholded image that separates an image
25246
into foreground and background components. The filter computes the
25247
threshold using the OtsuThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
25251
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
25252
de Jouy-en-Josas, France.
25254
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
25260
Separate foreground and background using Otsu's method
25263
HistogramThresholdImageFilter
25265
itk::simple::OtsuThreshold for the procedural interface
25267
itk::OtsuThresholdImageFilter for the Doxygen on the original ITK class.
25270
C++ includes: sitkOtsuThresholdImageFilter.h
25273
%feature("docstring") itk::simple::OtsuThresholdImageFilter::Execute "
25275
Execute the filter on the input image
25279
%feature("docstring") itk::simple::OtsuThresholdImageFilter::Execute "
25282
%feature("docstring") itk::simple::OtsuThresholdImageFilter::Execute "
25284
Execute the filter on the input image with the given parameters
25288
%feature("docstring") itk::simple::OtsuThresholdImageFilter::Execute "
25291
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetInsideValue "
25293
Get the \"inside\" pixel value.
25297
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetMaskOutput "
25300
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetMaskValue "
25303
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetName "
25309
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetNumberOfHistogramBins "
25312
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetOutsideValue "
25314
Get the \"outside\" pixel value.
25318
%feature("docstring") itk::simple::OtsuThresholdImageFilter::GetThreshold "
25320
Get the computed threshold.
25323
This is a measurement. Its value is updated in the Execute methods, so
25324
the value will only be valid after an execution.
25328
%feature("docstring") itk::simple::OtsuThresholdImageFilter::MaskOutputOff "
25331
%feature("docstring") itk::simple::OtsuThresholdImageFilter::MaskOutputOn "
25333
Set the value of MaskOutput to true or false respectfully.
25337
%feature("docstring") itk::simple::OtsuThresholdImageFilter::OtsuThresholdImageFilter "
25339
Default Constructor that takes no arguments and initializes default
25344
%feature("docstring") itk::simple::OtsuThresholdImageFilter::SetInsideValue "
25346
Set the \"inside\" pixel value. The default value NumericTraits<OutputPixelType>::max()
25350
%feature("docstring") itk::simple::OtsuThresholdImageFilter::SetMaskOutput "
25352
Do you want the output to be masked by the mask used in histogram
25353
construction. Only relevant if masking is in use.
25357
%feature("docstring") itk::simple::OtsuThresholdImageFilter::SetMaskValue "
25359
The value in the mask image, if used, indicating voxels that should be
25360
included. Default is the max of pixel type, as in the
25361
MaskedImageToHistogramFilter
25365
%feature("docstring") itk::simple::OtsuThresholdImageFilter::SetNumberOfHistogramBins "
25367
Set/Get the number of histogram bins. Defaults is 128.
25371
%feature("docstring") itk::simple::OtsuThresholdImageFilter::SetOutsideValue "
25373
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
25377
%feature("docstring") itk::simple::OtsuThresholdImageFilter::ToString "
25379
Print ourselves out
25383
%feature("docstring") itk::simple::OtsuThresholdImageFilter::~OtsuThresholdImageFilter "
25390
%feature("docstring") itk::simple::PasteImageFilter "
25392
Paste an image into another image.
25395
PasteImageFilter allows you to take a section of one image and paste into another
25396
image. The SetDestinationIndex() method prescribes where in the first input to start pasting data from
25397
the second input. The SetSourceRegion method prescribes the section of
25398
the second image to paste into the first. If the output requested
25399
region does not include the SourceRegion after it has been
25400
repositioned to DestinationIndex, then the output will just be a copy
25403
The two inputs and output image will have the same pixel type.
25409
Paste a part of one image into another image
25411
itk::simple::Paste for the procedural interface
25413
itk::PasteImageFilter for the Doxygen on the original ITK class.
25417
C++ includes: sitkPasteImageFilter.h
25420
%feature("docstring") itk::simple::PasteImageFilter::Execute "
25422
Execute the filter on the input images
25426
%feature("docstring") itk::simple::PasteImageFilter::Execute "
25428
Execute the filter on the input images with the given parameters
25432
%feature("docstring") itk::simple::PasteImageFilter::GetDestinationIndex "
25434
Set/Get the destination index (where in the first input the second
25435
input will be pasted.
25439
%feature("docstring") itk::simple::PasteImageFilter::GetName "
25445
%feature("docstring") itk::simple::PasteImageFilter::GetSourceIndex "
25448
%feature("docstring") itk::simple::PasteImageFilter::GetSourceSize "
25451
%feature("docstring") itk::simple::PasteImageFilter::PasteImageFilter "
25453
Default Constructor that takes no arguments and initializes default
25458
%feature("docstring") itk::simple::PasteImageFilter::SetDestinationIndex "
25460
Set/Get the destination index (where in the first input the second
25461
input will be pasted.
25465
%feature("docstring") itk::simple::PasteImageFilter::SetSourceIndex "
25468
%feature("docstring") itk::simple::PasteImageFilter::SetSourceSize "
25471
%feature("docstring") itk::simple::PasteImageFilter::ToString "
25473
Print ourselves out
25477
%feature("docstring") itk::simple::PasteImageFilter::~PasteImageFilter "
25484
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter "
25486
Derived class implementing a specific patch-based denoising algorithm,
25490
This class is derived from the base class PatchBasedDenoisingBaseImageFilter ; please refer to the documentation of the base class first. This
25491
class implements a denoising filter that uses iterative non-local, or
25492
semi-local, weighted averaging of image patches for image denoising.
25493
The intensity at each pixel 'p' gets updated as a weighted average of
25494
intensities of a chosen subset of pixels from the image.
25496
This class implements the denoising algorithm using a Gaussian kernel
25497
function for nonparametric density estimation. The class implements a
25498
scheme to automatically estimated the kernel bandwidth parameter
25499
(namely, sigma) using leave-one-out cross validation. It implements
25500
schemes for random sampling of patches non-locally (from the entire
25501
image) as well as semi-locally (from the spatial proximity of the
25502
pixel being denoised at the specific point in time). It implements a
25503
specific scheme for defining patch weights (mask) as described in
25504
Awate and Whitaker 2005 IEEE CVPR and 2006 IEEE TPAMI.
25508
PatchBasedDenoisingBaseImageFilter
25510
itk::PatchBasedDenoisingImageFilter for the Doxygen on the original ITK class.
25513
C++ includes: sitkPatchBasedDenoisingImageFilter.h
25516
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::AlwaysTreatComponentsAsEuclideanOff "
25519
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::AlwaysTreatComponentsAsEuclideanOn "
25521
Set the value of AlwaysTreatComponentsAsEuclidean to true or false
25526
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::Execute "
25528
Execute the filter on the input image
25532
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::Execute "
25534
Execute the filter on the input image with the given parameters
25538
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetAlwaysTreatComponentsAsEuclidean "
25540
Set/Get flag indicating whether all components should always be
25541
treated as if they are in euclidean space regardless of pixel type.
25546
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetKernelBandwidthEstimation "
25548
Set/Get flag indicating whether kernel-bandwidth should be estimated
25549
automatically from the image data. Defaults to true.
25553
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetKernelBandwidthFractionPixelsForEstimation "
25555
Set/Get the fraction of the image to use for kernel bandwidth sigma
25556
estimation. To reduce the computational burden for computing sigma, a
25557
small random fraction of the image pixels can be used.
25561
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetKernelBandwidthMultiplicationFactor "
25563
Set/Get the kernel bandwidth sigma multiplication factor used to
25564
modify the automatically-estimated kernel bandwidth sigma. At times,
25565
it may be desirable to modify the value of the automatically-estimated
25566
sigma. Typically, this number isn't very far from 1. Note: This is
25567
used only when KernelBandwidthEstimation is True/On.
25571
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetKernelBandwidthSigma "
25573
Set/Get initial kernel bandwidth estimate. To prevent the class from
25574
automatically modifying this estimate, set KernelBandwidthEstimation
25575
to false in the base class.
25579
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetKernelBandwidthUpdateFrequency "
25581
Set/Get the update frequency for the kernel bandwidth estimation. An
25582
optimal bandwidth will be re-estimated based on the denoised image
25583
after every 'n' iterations. Must be a positive integer. Defaults to 3,
25584
i.e. bandwidth updated after every 3 denoising iteration.
25588
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetName "
25594
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetNoiseModel "
25596
Set/Get the noise model type. Defaults to GAUSSIAN. To use the noise
25597
model during denoising, FidelityWeight must be positive.
25601
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetNoiseModelFidelityWeight "
25603
Set/Get the weight on the fidelity term (penalizes deviations from the
25604
noisy data). This option is used when a noise model is specified. This
25605
weight controls the balance between the smoothing and the closeness to
25610
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetNoiseSigma "
25613
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetNumberOfIterations "
25615
Set/Get the number of denoising iterations to perform. Must be a
25616
positive integer. Defaults to 1.
25620
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetNumberOfSamplePatches "
25623
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetPatchRadius "
25625
Set/Get the patch radius specified in physical coordinates. Patch
25626
radius is preferably set to an even number. Currently, only isotropic
25627
patches in physical space are allowed; patches can be anisotropic in
25632
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::GetSampleVariance "
25634
Set/Get the variance of the domain where patches are sampled.
25638
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::KernelBandwidthEstimationOff "
25641
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::KernelBandwidthEstimationOn "
25643
Set the value of KernelBandwidthEstimation to true or false
25648
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::PatchBasedDenoisingImageFilter "
25650
Default Constructor that takes no arguments and initializes default
25655
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetAlwaysTreatComponentsAsEuclidean "
25657
Set/Get flag indicating whether all components should always be
25658
treated as if they are in euclidean space regardless of pixel type.
25663
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetKernelBandwidthEstimation "
25665
Set/Get flag indicating whether kernel-bandwidth should be estimated
25666
automatically from the image data. Defaults to true.
25670
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetKernelBandwidthFractionPixelsForEstimation "
25672
Set/Get the fraction of the image to use for kernel bandwidth sigma
25673
estimation. To reduce the computational burden for computing sigma, a
25674
small random fraction of the image pixels can be used.
25678
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetKernelBandwidthMultiplicationFactor "
25680
Set/Get the kernel bandwidth sigma multiplication factor used to
25681
modify the automatically-estimated kernel bandwidth sigma. At times,
25682
it may be desirable to modify the value of the automatically-estimated
25683
sigma. Typically, this number isn't very far from 1. Note: This is
25684
used only when KernelBandwidthEstimation is True/On.
25688
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetKernelBandwidthSigma "
25690
Set/Get initial kernel bandwidth estimate. To prevent the class from
25691
automatically modifying this estimate, set KernelBandwidthEstimation
25692
to false in the base class.
25696
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetKernelBandwidthUpdateFrequency "
25698
Set/Get the update frequency for the kernel bandwidth estimation. An
25699
optimal bandwidth will be re-estimated based on the denoised image
25700
after every 'n' iterations. Must be a positive integer. Defaults to 3,
25701
i.e. bandwidth updated after every 3 denoising iteration.
25705
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetNoiseModel "
25707
Set/Get the noise model type. Defaults to GAUSSIAN. To use the noise
25708
model during denoising, FidelityWeight must be positive.
25712
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetNoiseModelFidelityWeight "
25714
Set/Get the weight on the fidelity term (penalizes deviations from the
25715
noisy data). This option is used when a noise model is specified. This
25716
weight controls the balance between the smoothing and the closeness to
25721
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetNoiseSigma "
25723
Set/Get the noise sigma. Used by the noise model where appropriate,
25724
defaults to 5% of the image intensity range
25728
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetNumberOfIterations "
25730
Set/Get the number of denoising iterations to perform. Must be a
25731
positive integer. Defaults to 1.
25735
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetNumberOfSamplePatches "
25737
Set/Get the number of patches to sample for each pixel.
25741
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetPatchRadius "
25743
Set/Get the patch radius specified in physical coordinates. Patch
25744
radius is preferably set to an even number. Currently, only isotropic
25745
patches in physical space are allowed; patches can be anisotropic in
25750
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::SetSampleVariance "
25752
Set/Get the variance of the domain where patches are sampled.
25756
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::ToString "
25758
Print ourselves out
25762
%feature("docstring") itk::simple::PatchBasedDenoisingImageFilter::~PatchBasedDenoisingImageFilter "
25769
%feature("docstring") itk::simple::PermuteAxesImageFilter "
25771
Permutes the image axes according to a user specified order.
25774
PermuateAxesImageFilter permutes the image axes according to a user
25775
specified order. The permutation order is set via method SetOrder(
25776
order ) where the input is an array of ImageDimension number of
25777
unsigned int. The elements of the array must be a rearrangment of the
25778
numbers from 0 to ImageDimension - 1.
25780
The i-th axis of the output image corresponds with the order[i]-th
25781
axis of the input image.
25783
The output meta image information (LargestPossibleRegion, spacing,
25784
origin) is computed by permuting the corresponding input meta
25791
Switch the axes of an image
25793
itk::simple::PermuteAxes for the procedural interface
25795
itk::PermuteAxesImageFilter for the Doxygen on the original ITK class.
25799
C++ includes: sitkPermuteAxesImageFilter.h
25802
%feature("docstring") itk::simple::PermuteAxesImageFilter::Execute "
25804
Execute the filter on the input image
25808
%feature("docstring") itk::simple::PermuteAxesImageFilter::Execute "
25810
Execute the filter on the input image with the given parameters
25814
%feature("docstring") itk::simple::PermuteAxesImageFilter::GetName "
25820
%feature("docstring") itk::simple::PermuteAxesImageFilter::GetOrder "
25822
Get the permutation order.
25826
%feature("docstring") itk::simple::PermuteAxesImageFilter::PermuteAxesImageFilter "
25828
Default Constructor that takes no arguments and initializes default
25833
%feature("docstring") itk::simple::PermuteAxesImageFilter::SetOrder "
25835
Set the permutation order. The elements of order must be a
25836
rearrangement of the numbers from 0 to ImageDimension - 1.
25840
%feature("docstring") itk::simple::PermuteAxesImageFilter::ToString "
25842
Print ourselves out
25846
%feature("docstring") itk::simple::PermuteAxesImageFilter::~PermuteAxesImageFilter "
25853
%feature("docstring") itk::simple::PhysicalPointImageSource "
25855
Generate an image of the physical locations of each pixel.
25858
This image source supports image which have a multi-component pixel
25859
equal to the image dimension, and variable length VectorImages. It is
25860
recommended that the component type be a real valued type.
25862
itk::simple::PhysicalPointImageSource for the procedural interface
25864
itk::PhysicalPointImageSource for the Doxygen on the original ITK class.
25867
C++ includes: sitkPhysicalPointImageSource.h
25870
%feature("docstring") itk::simple::PhysicalPointImageSource::Execute "
25872
Execute the filter on the input image
25876
%feature("docstring") itk::simple::PhysicalPointImageSource::Execute "
25878
Execute the filter on the input image with the given parameters
25882
%feature("docstring") itk::simple::PhysicalPointImageSource::GetDirection "
25885
%feature("docstring") itk::simple::PhysicalPointImageSource::GetName "
25891
%feature("docstring") itk::simple::PhysicalPointImageSource::GetOrigin "
25894
%feature("docstring") itk::simple::PhysicalPointImageSource::GetOutputPixelType "
25897
%feature("docstring") itk::simple::PhysicalPointImageSource::GetSize "
25900
%feature("docstring") itk::simple::PhysicalPointImageSource::GetSpacing "
25903
%feature("docstring") itk::simple::PhysicalPointImageSource::PhysicalPointImageSource "
25905
Default Constructor that takes no arguments and initializes default
25910
%feature("docstring") itk::simple::PhysicalPointImageSource::SetDirection "
25913
%feature("docstring") itk::simple::PhysicalPointImageSource::SetOrigin "
25916
%feature("docstring") itk::simple::PhysicalPointImageSource::SetOutputPixelType "
25919
%feature("docstring") itk::simple::PhysicalPointImageSource::SetReferenceImage "
25921
This methods sets the size, origin, spacing and direction to that of
25926
%feature("docstring") itk::simple::PhysicalPointImageSource::SetSize "
25929
%feature("docstring") itk::simple::PhysicalPointImageSource::SetSpacing "
25932
%feature("docstring") itk::simple::PhysicalPointImageSource::ToString "
25934
Print ourselves out
25938
%feature("docstring") itk::simple::PhysicalPointImageSource::~PhysicalPointImageSource "
25945
%feature("docstring") itk::simple::PimpleImageBase "
25947
Private implementation idiom image base class.
25950
We utilize the private implementation ( or PImple) programming idiom
25951
to modify the behavior of the simple image class based on the
25952
different image types.
25954
This class is designed to utilize the trivial copy, and assgnement
25957
C++ includes: sitkPimpleImageBase.h
25960
%feature("docstring") itk::simple::PimpleImageBase::DeepCopy "
25963
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsDouble "
25966
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsDouble "
25969
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsFloat "
25972
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsFloat "
25975
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt16 "
25978
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt16 "
25981
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt32 "
25984
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt32 "
25987
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt64 "
25990
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt64 "
25993
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt8 "
25996
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsInt8 "
25999
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt16 "
26002
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt16 "
26005
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt32 "
26008
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt32 "
26011
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt64 "
26014
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt64 "
26017
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt8 "
26020
%feature("docstring") itk::simple::PimpleImageBase::GetBufferAsUInt8 "
26023
%feature("docstring") itk::simple::PimpleImageBase::GetDataBase "
26026
%feature("docstring") itk::simple::PimpleImageBase::GetDataBase "
26029
%feature("docstring") itk::simple::PimpleImageBase::GetDepth "
26032
%feature("docstring") itk::simple::PimpleImageBase::GetDimension "
26035
%feature("docstring") itk::simple::PimpleImageBase::GetDirection "
26038
%feature("docstring") itk::simple::PimpleImageBase::GetHeight "
26041
%feature("docstring") itk::simple::PimpleImageBase::GetNumberOfComponentsPerPixel "
26044
%feature("docstring") itk::simple::PimpleImageBase::GetNumberOfPixels "
26047
%feature("docstring") itk::simple::PimpleImageBase::GetOrigin "
26050
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsComplexFloat32 "
26053
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsComplexFloat64 "
26056
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsDouble "
26059
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsFloat "
26062
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsInt16 "
26065
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsInt32 "
26068
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsInt64 "
26071
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsInt8 "
26074
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsUInt16 "
26077
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsUInt32 "
26080
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsUInt64 "
26083
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsUInt8 "
26086
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorFloat32 "
26089
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorFloat64 "
26092
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorInt16 "
26095
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorInt32 "
26098
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorInt64 "
26101
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorInt8 "
26104
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorUInt16 "
26107
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorUInt32 "
26110
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorUInt64 "
26113
%feature("docstring") itk::simple::PimpleImageBase::GetPixelAsVectorUInt8 "
26116
%feature("docstring") itk::simple::PimpleImageBase::GetPixelID "
26119
%feature("docstring") itk::simple::PimpleImageBase::GetReferenceCountOfImage "
26122
%feature("docstring") itk::simple::PimpleImageBase::GetSize "
26125
%feature("docstring") itk::simple::PimpleImageBase::GetSize "
26128
%feature("docstring") itk::simple::PimpleImageBase::GetSpacing "
26131
%feature("docstring") itk::simple::PimpleImageBase::GetWidth "
26134
%feature("docstring") itk::simple::PimpleImageBase::SetDirection "
26137
%feature("docstring") itk::simple::PimpleImageBase::SetOrigin "
26140
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsComplexFloat32 "
26143
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsComplexFloat64 "
26146
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsDouble "
26149
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsFloat "
26152
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsInt16 "
26155
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsInt32 "
26158
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsInt64 "
26161
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsInt8 "
26164
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsUInt16 "
26167
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsUInt32 "
26170
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsUInt64 "
26173
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsUInt8 "
26176
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorFloat32 "
26179
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorFloat64 "
26182
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorInt16 "
26185
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorInt32 "
26188
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorInt64 "
26191
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorInt8 "
26194
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorUInt16 "
26197
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorUInt32 "
26200
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorUInt64 "
26203
%feature("docstring") itk::simple::PimpleImageBase::SetPixelAsVectorUInt8 "
26206
%feature("docstring") itk::simple::PimpleImageBase::SetSpacing "
26209
%feature("docstring") itk::simple::PimpleImageBase::ShallowCopy "
26212
%feature("docstring") itk::simple::PimpleImageBase::ToString "
26215
%feature("docstring") itk::simple::PimpleImageBase::TransformContinuousIndexToPhysicalPoint "
26218
%feature("docstring") itk::simple::PimpleImageBase::TransformIndexToPhysicalPoint "
26221
%feature("docstring") itk::simple::PimpleImageBase::TransformPhysicalPointToContinuousIndex "
26224
%feature("docstring") itk::simple::PimpleImageBase::TransformPhysicalPointToIndex "
26227
%feature("docstring") itk::simple::PimpleImageBase::~PimpleImageBase "
26231
%feature("docstring") itk::simple::PowImageFilter "
26233
Computes the powers of 2 images.
26236
This class is templated over the types of the two input images and the
26237
type of the output image. Numeric conversions (castings) are done by
26240
The output of the pow function will be cast to the pixel type of the
26243
The total operation over one pixel will be
26245
The pow function can be applied to two images with the following:
26247
Additionally, this filter can be used to raise every pixel of an image
26248
to a power of a constant by using
26250
itk::simple::Pow for the procedural interface
26252
itk::PowImageFilter for the Doxygen on the original ITK class.
26255
C++ includes: sitkPowImageFilter.h
26258
%feature("docstring") itk::simple::PowImageFilter::Execute "
26260
Execute the filter on the input images
26264
%feature("docstring") itk::simple::PowImageFilter::Execute "
26266
Execute the filter with an image and a constant
26270
%feature("docstring") itk::simple::PowImageFilter::Execute "
26273
%feature("docstring") itk::simple::PowImageFilter::GetName "
26279
%feature("docstring") itk::simple::PowImageFilter::PowImageFilter "
26281
Default Constructor that takes no arguments and initializes default
26286
%feature("docstring") itk::simple::PowImageFilter::ToString "
26288
Print ourselves out
26292
%feature("docstring") itk::simple::PowImageFilter::~PowImageFilter "
26299
%feature("docstring") itk::simple::ProcessObject "
26301
Base class for SimpleITK classes based on ProcessObject.
26303
C++ includes: sitkProcessObject.h
26306
%feature("docstring") itk::simple::ProcessObject::Abort "
26308
Sets an abort flag on the active process.
26310
Requests the current active process to abort. Additional, progress or
26311
iteration event may occur. If aborted then, an AbortEvent should
26312
occur. The Progress should be set to 1.0 after aborting.
26314
The expected behavior is that not exception should be throw out of
26315
this processes Execute method. Additionally, the results returned are
26316
valid but undefined content. The content may be only partially
26317
updated, uninitialized or the a of size zero.
26319
If there is no active process the method has no effect.
26323
%feature("docstring") itk::simple::ProcessObject::AddCommand "
26325
Add a Command Object to observer the event.
26328
The Command object's Execute method will be invoked when the internal ITK Object has the event. These events only occur during this ProcessObject's Execute method when the ITK filter is running. The command occurs
26329
in the same thread as this objects Execute methods was called in.
26331
An internal reference is made between the Command and this ProcessObject which enable automatic removal of the command when deleted. This
26332
enables both object to exist as stack based object and be
26333
automatically cleaned up.
26335
Unless specified otherwise, it's safe to get any value during
26336
execution. \"Measurements\" will have valid values only after the
26337
Execute method has returned. \"Active Measurements\" will have valid
26338
values during events, and access the underlying ITK object.
26340
Deleting a command this object has during a command call-back will
26341
produce undefined behavior.
26343
For more information see the page Commands and Events for SimpleITK.
26346
The return value is reserved for latter usage.
26351
%feature("docstring") itk::simple::ProcessObject::GetName "
26353
return user readable name for the filter
26357
%feature("docstring") itk::simple::ProcessObject::GetProgress "
26359
An Active Measurement of the progress of execution.
26362
Get the execution progress of the current process object. The progress
26363
is a floating number in [0,1] with 0 meaning no progress and 1 meaning
26364
the filter has completed execution (or aborted).
26366
This is an Active Measurement so it can be accessed during Events
26367
during the execution.
26371
%feature("docstring") itk::simple::ProcessObject::HasCommand "
26373
Query of this object has any registered commands for event.
26377
%feature("docstring") itk::simple::ProcessObject::ProcessObject "
26379
Default Constructor that takes no arguments and initializes default
26384
%feature("docstring") itk::simple::ProcessObject::RemoveAllCommands "
26386
Remove all registered commands.
26389
Calling when this object is invoking anther command will produce
26390
undefined behavior.
26394
%feature("docstring") itk::simple::ProcessObject::ToString "
26397
%feature("docstring") itk::simple::ProcessObject::~ProcessObject "
26404
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter "
26406
Deconvolve an image using the projected Landweber deconvolution
26410
This filter performs the same calculation per iteration as the LandweberDeconvolutionImageFilter . However, at each iteration, negative pixels in the intermediate
26411
result are projected (set) to zero. This is useful if the solution is
26412
assumed to always be non-negative, which is the case when dealing with
26413
images formed by counting photons, for example.
26415
This code was adapted from the Insight Journal contribution:
26417
\"Deconvolution: infrastructure and reference algorithms\" by Gaetan
26418
Lehmann https://hdl.handle.net/10380/3207
26421
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
26422
de Jouy-en-Josas, France
26423
Cory Quammen, The University of North Carolina at Chapel Hill
26427
IterativeDeconvolutionImageFilter
26429
RichardsonLucyDeconvolutionImageFilter
26431
LandweberDeconvolutionImageFilter
26433
itk::simple::ProjectedLandweberDeconvolution for the procedural interface
26435
itk::ProjectedLandweberDeconvolutionImageFilter for the Doxygen on the original ITK class.
26438
C++ includes: sitkProjectedLandweberDeconvolutionImageFilter.h
26441
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::Execute "
26443
Execute the filter on the input images
26447
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::Execute "
26449
Execute the filter on the input images with the given parameters
26453
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetAlpha "
26455
Get the relaxation factor.
26459
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetBoundaryCondition "
26462
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetName "
26468
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetNormalize "
26471
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetNumberOfIterations "
26473
Get the number of iterations.
26477
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::GetOutputRegionMode "
26480
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::NormalizeOff "
26483
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::NormalizeOn "
26485
Set the value of Normalize to true or false respectfully.
26489
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::ProjectedLandweberDeconvolutionImageFilter "
26491
Default Constructor that takes no arguments and initializes default
26496
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetAlpha "
26498
Set the relaxation factor.
26502
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetBoundaryCondition "
26505
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetNormalize "
26507
Normalize the output image by the sum of the kernel components
26511
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetNumberOfIterations "
26513
Set the number of iterations.
26517
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::SetOutputRegionMode "
26520
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::ToString "
26522
Print ourselves out
26526
%feature("docstring") itk::simple::ProjectedLandweberDeconvolutionImageFilter::~ProjectedLandweberDeconvolutionImageFilter "
26533
%feature("docstring") itk::simple::RankImageFilter "
26535
Rank filter of a greyscale image.
26538
Nonlinear filter in which each output pixel is a user defined rank of
26539
input pixels in a user defined neighborhood. The default rank is 0.5
26540
(median). The boundary conditions are different to the standard
26541
itkMedianImageFilter. In this filter the neighborhood is cropped at
26542
the boundary, and is therefore smaller.
26544
This filter uses a recursive implementation - essentially the one by
26545
Huang 1979, I believe, to compute the rank, and is therefore usually a
26546
lot faster than the direct implementation. The extensions to Huang are
26547
support for arbitrary pixel types (using c++ maps) and arbitrary
26548
neighborhoods. I presume that these are not new ideas.
26550
This filter is based on the sliding window code from the
26551
consolidatedMorphology package on InsightJournal.
26553
The structuring element is assumed to be composed of binary values
26554
(zero or one). Only elements of the structuring element having values
26555
> 0 are candidates for affecting the center pixel.
26557
This code was contributed in the Insight Journal paper: \"Efficient
26558
implementation of kernel filtering\" by Beare R., Lehmann G https://hdl.handle.net/1926/555 http://www.insight-journal.org/browse/publication/160
26564
itk::simple::Rank for the procedural interface
26566
itk::RankImageFilter for the Doxygen on the original ITK class.
26569
C++ includes: sitkRankImageFilter.h
26572
%feature("docstring") itk::simple::RankImageFilter::Execute "
26574
Execute the filter on the input image
26578
%feature("docstring") itk::simple::RankImageFilter::Execute "
26580
Execute the filter on the input image with the given parameters
26584
%feature("docstring") itk::simple::RankImageFilter::GetName "
26590
%feature("docstring") itk::simple::RankImageFilter::GetRadius "
26593
%feature("docstring") itk::simple::RankImageFilter::GetRank "
26596
%feature("docstring") itk::simple::RankImageFilter::RankImageFilter "
26598
Default Constructor that takes no arguments and initializes default
26603
%feature("docstring") itk::simple::RankImageFilter::SetRadius "
26606
%feature("docstring") itk::simple::RankImageFilter::SetRadius "
26608
Set the values of the Radius vector all to value
26612
%feature("docstring") itk::simple::RankImageFilter::SetRank "
26615
%feature("docstring") itk::simple::RankImageFilter::ToString "
26617
Print ourselves out
26621
%feature("docstring") itk::simple::RankImageFilter::~RankImageFilter "
26628
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter "
26630
ComposeImageFilter combine several scalar images into a multicomponent image.
26633
ComposeImageFilter combine several scalar images into an itk::Image of vector pixel ( itk::Vector , itk::RGBPixel , ...), of std::complex pixel, or in an itk::VectorImage .
26636
All input images are expected to have the same template parameters
26637
and have the same size and origin.
26642
VectorIndexSelectionCastImageFilter
26647
Create a vector image from a collection of scalar images
26649
Compose a vector image (with 3 components) from three scalar images
26651
Convert a real image and an imaginary image to a complex image
26653
itk::simple::RealAndImaginaryToComplex for the procedural interface
26655
itk::ComposeImageFilter for the Doxygen on the original ITK class.
26659
C++ includes: sitkRealAndImaginaryToComplexImageFilter.h
26662
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter::Execute "
26664
Execute the filter on the input images
26668
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter::GetName "
26674
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter::RealAndImaginaryToComplexImageFilter "
26676
Default Constructor that takes no arguments and initializes default
26681
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter::ToString "
26683
Print ourselves out
26687
%feature("docstring") itk::simple::RealAndImaginaryToComplexImageFilter::~RealAndImaginaryToComplexImageFilter "
26694
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter "
26696
Base class for specialized real-to-complex forward Fast Fourier Transform .
26699
This is a base class for the \"forward\" or \"direct\" discrete
26700
Fourier Transform . This is an abstract base class: the actual implementation is
26701
provided by the best child class available on the system when the
26702
object is created via the object factory system.
26704
This class transforms a real input image into its complex Fourier
26705
transform. The Fourier transform of a real input image has Hermitian
26706
symmetry: $ f(\\\\mathbf{x}) = f^*(-\\\\mathbf{x}) $ . That is, when the result of the transform is split in half along
26707
the X-dimension, the values in the second half of the transform are
26708
the complex conjugates of values in the first half reflected about the
26709
center of the image in each dimension. This filter takes advantage of
26710
the Hermitian symmetry property and reduces the size of the output in
26711
the first dimension to N/2+1, where N is the size of the input image
26712
in that dimension and the division by 2 is rounded down.
26716
HalfHermitianToRealInverseFFTImageFilter
26718
ForwardFFTImageFilter
26720
itk::simple::RealToHalfHermitianForwardFFT for the procedural interface
26722
itk::RealToHalfHermitianForwardFFTImageFilter for the Doxygen on the original ITK class.
26725
C++ includes: sitkRealToHalfHermitianForwardFFTImageFilter.h
26728
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter::Execute "
26730
Execute the filter on the input image
26734
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter::GetName "
26740
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter::RealToHalfHermitianForwardFFTImageFilter "
26742
Default Constructor that takes no arguments and initializes default
26747
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter::ToString "
26749
Print ourselves out
26753
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFTImageFilter::~RealToHalfHermitianForwardFFTImageFilter "
26760
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter "
26762
grayscale reconstruction by dilation of an image
26765
Reconstruction by dilation operates on a \"marker\" image and a
26766
\"mask\" image, and is defined as the dilation of the marker image
26767
with respect to the mask image iterated until stability.
26769
The marker image must be less than or equal to the mask image (on a
26770
pixel by pixel basis).
26772
Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
26773
book \"Morphological Image Analysis: Principles and Applications\",
26774
Second Edition, Springer, 2003.
26776
Algorithm implemented in this filter is based on algorithm described
26777
by Kevin Robinson and Paul F. Whelan in \"Efficient Morphological
26778
Reconstruction: A Downhill Filter\", Pattern Recognition Letters,
26779
Volume 25, Issue 15, November 2004, Pages 1759-1767.
26781
The algorithm, a description of the transform and some applications
26782
can be found in \"Morphological Grayscale Reconstruction in Image
26783
Analysis: Applications and Efficient Algorithms\", Luc Vincent, IEEE
26784
Transactions on image processing, Vol. 2, April 1993.
26787
Richard Beare. Department of Medicine, Monash University, Melbourne,
26791
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter , ReconstructionByErosionImageFilter , OpeningByReconstructionImageFilter , ClosingByReconstructionImageFilter , ReconstructionImageFilter
26793
itk::simple::ReconstructionByDilation for the procedural interface
26795
itk::ReconstructionByDilationImageFilter for the Doxygen on the original ITK class.
26798
C++ includes: sitkReconstructionByDilationImageFilter.h
26801
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::Execute "
26803
Execute the filter on the input images
26807
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::Execute "
26809
Execute the filter on the input images with the given parameters
26813
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::FullyConnectedOff "
26816
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::FullyConnectedOn "
26818
Set the value of FullyConnected to true or false respectfully.
26822
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::GetFullyConnected "
26825
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::GetName "
26831
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::GetUseInternalCopy "
26834
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::ReconstructionByDilationImageFilter "
26836
Default Constructor that takes no arguments and initializes default
26841
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::SetFullyConnected "
26844
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::SetUseInternalCopy "
26847
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::ToString "
26849
Print ourselves out
26853
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::UseInternalCopyOff "
26856
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::UseInternalCopyOn "
26858
Set the value of UseInternalCopy to true or false respectfully.
26862
%feature("docstring") itk::simple::ReconstructionByDilationImageFilter::~ReconstructionByDilationImageFilter "
26869
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter "
26871
grayscale reconstruction by erosion of an image
26874
Reconstruction by erosion operates on a \"marker\" image and a
26875
\"mask\" image, and is defined as the erosion of the marker image with
26876
respect to the mask image iterated until stability.
26878
The marker image must be less than or equal to the mask image (on a
26879
pixel by pixel basis).
26881
Geodesic morphology is described in Chapter 6.2 of Pierre Soille's
26882
book \"Morphological Image Analysis: Principles and Applications\",
26883
Second Edition, Springer, 2003.
26885
Algorithm implemented in this filter is based on algorithm described
26886
by Kevin Robinson and Paul F. Whelan in \"Efficient Morphological
26887
Reconstruction: A Downhill Filter\", Pattern Recognition Letters,
26888
Volume 25, Issue 15, November 2004, Pages 1759-1767.
26890
The algorithm, a description of the transform and some applications
26891
can be found in \"Morphological Grayscale Reconstruction in Image
26892
Analysis: Applications and Efficient Algorithms\", Luc Vincent, IEEE
26893
Transactions on image processing, Vol. 2, April 1993.
26896
Richard Beare. Department of Medicine, Monash University, Melbourne,
26900
MorphologyImageFilter , GrayscaleDilateImageFilter , GrayscaleFunctionDilateImageFilter , BinaryDilateImageFilter , ReconstructionByErosionImageFilter , OpeningByReconstructionImageFilter , ClosingByReconstructionImageFilter , ReconstructionImageFilter
26902
itk::simple::ReconstructionByErosion for the procedural interface
26904
itk::ReconstructionByErosionImageFilter for the Doxygen on the original ITK class.
26907
C++ includes: sitkReconstructionByErosionImageFilter.h
26910
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::Execute "
26912
Execute the filter on the input images
26916
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::Execute "
26918
Execute the filter on the input images with the given parameters
26922
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::FullyConnectedOff "
26925
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::FullyConnectedOn "
26927
Set the value of FullyConnected to true or false respectfully.
26931
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::GetFullyConnected "
26934
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::GetName "
26940
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::GetUseInternalCopy "
26943
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::ReconstructionByErosionImageFilter "
26945
Default Constructor that takes no arguments and initializes default
26950
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::SetFullyConnected "
26953
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::SetUseInternalCopy "
26956
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::ToString "
26958
Print ourselves out
26962
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::UseInternalCopyOff "
26965
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::UseInternalCopyOn "
26967
Set the value of UseInternalCopy to true or false respectfully.
26971
%feature("docstring") itk::simple::ReconstructionByErosionImageFilter::~ReconstructionByErosionImageFilter "
26978
%feature("docstring") itk::simple::RecursiveGaussianImageFilter "
26980
Base class for computing IIR convolution with an approximation of a
26984
\\\\[ \\\\frac{ 1 }{ \\\\sigma \\\\sqrt{ 2 \\\\pi } } \\\\exp{
26985
\\\\left( - \\\\frac{x^2}{ 2 \\\\sigma^2 } \\\\right) } \\\\]
26987
RecursiveGaussianImageFilter is the base class for recursive filters that approximate convolution
26988
with the Gaussian kernel. This class implements the recursive
26989
filtering method proposed by R.Deriche in IEEE-PAMI Vol.12, No.1,
26990
January 1990, pp 78-87, \"Fast Algorithms for Low-Level Vision\"
26992
Details of the implementation are described in the technical report: R.
26993
Deriche, \"Recursively Implementing The Gaussian and Its
26994
Derivatives\", INRIA, 1993, ftp://ftp.inria.fr/INRIA/tech-reports/RR/RR-1893.ps.gz
26996
Further improvements of the algorithm are described in: G. Farneback &
26997
C.-F. Westin, \"On Implementation of Recursive Gaussian Filters\", so
27000
As compared to itk::DiscreteGaussianImageFilter , this filter tends to be faster for large kernels, and it can take
27001
the derivative of the blurred image in one step. Also, note that we
27002
have itk::RecursiveGaussianImageFilter::SetSigma() , but itk::DiscreteGaussianImageFilter::SetVariance() .
27006
DiscreteGaussianImageFilter
27011
Find higher derivatives of an image
27013
itk::simple::RecursiveGaussian for the procedural interface
27015
itk::RecursiveGaussianImageFilter for the Doxygen on the original ITK class.
27019
C++ includes: sitkRecursiveGaussianImageFilter.h
27022
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::Execute "
27024
Execute the filter on the input image
27028
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::Execute "
27030
Execute the filter on the input image with the given parameters
27034
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::GetDirection "
27037
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::GetName "
27043
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::GetNormalizeAcrossScale "
27046
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::GetOrder "
27048
Set/Get the Order of the Gaussian to convolve with.
27051
ZeroOrder is equivalent to convolving with a Gaussian. This is the
27054
FirstOrder is equivalent to convolving with the first derivative of a
27057
SecondOrder is equivalent to convolving with the second derivative of
27063
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::GetSigma "
27065
Set/Get the Sigma, measured in world coordinates, of the Gaussian
27066
kernel. The default is 1.0. An exception will be generated if the
27067
Sigma value is less than or equal to zero.
27071
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::NormalizeAcrossScaleOff "
27074
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::NormalizeAcrossScaleOn "
27076
Set the value of NormalizeAcrossScale to true or false respectfully.
27080
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::RecursiveGaussianImageFilter "
27082
Default Constructor that takes no arguments and initializes default
27087
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::SetDirection "
27090
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::SetNormalizeAcrossScale "
27092
Set/Get the flag for normalizing the gaussian over scale-space.
27094
This flag enables the analysis of the differential shape of features
27095
independent of their size ( both pixels and physical size ). Following
27096
the notation of Tony Lindeberg:
27098
Let \\\\[ L(x; t) = g(x; t) \\\\ast f(x) \\\\] be the scale-space representation of image \\\\[ f(x) \\\\] where \\\\[ g(x; t) = \\\\frac{1}{ \\\\sqrt{ 2 \\\\pi t} } \\\\exp{
27099
\\\\left( -\\\\frac{x^2}{ 2 t } \\\\right) } \\\\] is the Gaussian function and \\\\[\\\\ast\\\\] denotes convolution. This is a change from above with \\\\[ t = \\\\sigma^2 \\\\] .
27101
Then the normalized derivative operator for normalized coordinates
27104
\\\\[ \\\\partial_\\\\xi = \\\\sqrt{t} \\\\partial_x \\\\]
27106
The resulting scaling factor is \\\\[ \\\\sigma^N \\\\] where N is the order of the derivative.
27108
When this flag is ON the filter will be normalized in such a way that
27109
the values of derivatives are not biased by the size of the object.
27110
That is to say the maximum value a feature reaches across scale is
27111
independent of the scale of the object.
27113
For analyzing an image across scale-space you want to enable this
27114
flag. It is disabled by default.
27117
Not all scale space axioms are satisfied by this filter, some are only
27118
approximated. Particularly, at fine scales ( say less than 1 pixel )
27119
other methods such as a discrete Gaussian kernel should be considered.
27124
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::SetOrder "
27126
Set/Get the Order of the Gaussian to convolve with.
27129
ZeroOrder is equivalent to convolving with a Gaussian. This is the
27132
FirstOrder is equivalent to convolving with the first derivative of a
27135
SecondOrder is equivalent to convolving with the second derivative of
27141
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::SetSigma "
27143
Set/Get the Sigma, measured in world coordinates, of the Gaussian
27144
kernel. The default is 1.0. An exception will be generated if the
27145
Sigma value is less than or equal to zero.
27149
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::ToString "
27151
Print ourselves out
27155
%feature("docstring") itk::simple::RecursiveGaussianImageFilter::~RecursiveGaussianImageFilter "
27162
%feature("docstring") itk::simple::RegionOfInterestImageFilter "
27164
Extract a region of interest from the input image.
27167
Extract a region of interest from the input image or convert between itk::Image and RLEImage (a custom region can be used).
27169
This filter produces an output image of the same dimension as the
27170
input image. The user specifies the region of the input image that
27171
will be contained in the output image. The origin coordinates of the
27172
output images will be computed in such a way that if mapped to
27173
physical space, the output image will overlay the input image with
27174
perfect registration. In other words, a registration process between
27175
the output image and the input image will return an identity
27178
If you are interested in changing the dimension of the image, you may
27179
want to consider the ExtractImageFilter . For example for extracting a 2D image from a slice of a 3D image.
27181
The region to extract is set using the method SetRegionOfInterest.
27190
Extract a portion of an image (region of interest)
27191
This filter produces an output image of the same dimension as the
27192
input image. The user specifies the region of the input image that
27193
will be contained in the output image. The origin coordinates of the
27194
output images will be computed in such a way that if mapped to
27195
physical space, the output image will overlay the input image with
27196
perfect registration. In other words, a registration process between
27197
the output image and the input image will return an identity
27200
The region to extract is set using the method SetRegionOfInterest.
27202
Specialized for RLEImage .
27204
itk::simple::RegionOfInterest for the procedural interface
27206
itk::RegionOfInterestImageFilter for the Doxygen on the original ITK class.
27209
C++ includes: sitkRegionOfInterestImageFilter.h
27212
%feature("docstring") itk::simple::RegionOfInterestImageFilter::Execute "
27214
Execute the filter on the input image
27218
%feature("docstring") itk::simple::RegionOfInterestImageFilter::Execute "
27220
Execute the filter on the input image with the given parameters
27224
%feature("docstring") itk::simple::RegionOfInterestImageFilter::GetIndex "
27227
%feature("docstring") itk::simple::RegionOfInterestImageFilter::GetName "
27233
%feature("docstring") itk::simple::RegionOfInterestImageFilter::GetSize "
27236
%feature("docstring") itk::simple::RegionOfInterestImageFilter::RegionOfInterestImageFilter "
27238
Default Constructor that takes no arguments and initializes default
27243
%feature("docstring") itk::simple::RegionOfInterestImageFilter::SetIndex "
27245
odo the internal setting of the method need work!!!
27249
%feature("docstring") itk::simple::RegionOfInterestImageFilter::SetSize "
27252
%feature("docstring") itk::simple::RegionOfInterestImageFilter::ToString "
27254
Print ourselves out
27258
%feature("docstring") itk::simple::RegionOfInterestImageFilter::~RegionOfInterestImageFilter "
27265
%feature("docstring") itk::simple::RegionalMaximaImageFilter "
27267
Produce a binary image where foreground is the regional maxima of the
27271
Regional maxima are flat zones surrounded by pixels of lower value.
27273
If the input image is constant, the entire image can be considered as
27274
a maxima or not. The desired behavior can be selected with the SetFlatIsMaxima() method.
27278
This class was contributed to the Insight Journal by author Gaetan
27279
Lehmann. Biologie du Developpement et de la Reproduction, INRA de
27280
Jouy-en-Josas, France. The paper can be found at https://hdl.handle.net/1926/153
27284
ValuedRegionalMaximaImageFilter
27288
RegionalMinimaImageFilter
27293
RegionalMaximaImageFilter
27295
itk::simple::RegionalMaxima for the procedural interface
27297
itk::RegionalMaximaImageFilter for the Doxygen on the original ITK class.
27301
C++ includes: sitkRegionalMaximaImageFilter.h
27304
%feature("docstring") itk::simple::RegionalMaximaImageFilter::Execute "
27306
Execute the filter on the input image
27310
%feature("docstring") itk::simple::RegionalMaximaImageFilter::Execute "
27312
Execute the filter on the input image with the given parameters
27316
%feature("docstring") itk::simple::RegionalMaximaImageFilter::FlatIsMaximaOff "
27319
%feature("docstring") itk::simple::RegionalMaximaImageFilter::FlatIsMaximaOn "
27321
Set the value of FlatIsMaxima to true or false respectfully.
27325
%feature("docstring") itk::simple::RegionalMaximaImageFilter::FullyConnectedOff "
27328
%feature("docstring") itk::simple::RegionalMaximaImageFilter::FullyConnectedOn "
27330
Set the value of FullyConnected to true or false respectfully.
27334
%feature("docstring") itk::simple::RegionalMaximaImageFilter::GetBackgroundValue "
27336
Set/Get the value used as \"background\" in the output image. Defaults
27337
to NumericTraits<PixelType>::NonpositiveMin() .
27341
%feature("docstring") itk::simple::RegionalMaximaImageFilter::GetFlatIsMaxima "
27343
Set/Get wether a flat image must be considered as a maxima or not.
27348
%feature("docstring") itk::simple::RegionalMaximaImageFilter::GetForegroundValue "
27350
Set/Get the value in the output image to consider as \"foreground\".
27351
Defaults to maximum value of PixelType.
27355
%feature("docstring") itk::simple::RegionalMaximaImageFilter::GetFullyConnected "
27357
Set/Get whether the connected components are defined strictly by face
27358
connectivity or by face+edge+vertex connectivity. Default is
27359
FullyConnectedOff. For objects that are 1 pixel wide, use
27364
%feature("docstring") itk::simple::RegionalMaximaImageFilter::GetName "
27370
%feature("docstring") itk::simple::RegionalMaximaImageFilter::RegionalMaximaImageFilter "
27372
Default Constructor that takes no arguments and initializes default
27377
%feature("docstring") itk::simple::RegionalMaximaImageFilter::SetBackgroundValue "
27379
Set/Get the value used as \"background\" in the output image. Defaults
27380
to NumericTraits<PixelType>::NonpositiveMin() .
27384
%feature("docstring") itk::simple::RegionalMaximaImageFilter::SetFlatIsMaxima "
27386
Set/Get wether a flat image must be considered as a maxima or not.
27391
%feature("docstring") itk::simple::RegionalMaximaImageFilter::SetForegroundValue "
27393
Set/Get the value in the output image to consider as \"foreground\".
27394
Defaults to maximum value of PixelType.
27398
%feature("docstring") itk::simple::RegionalMaximaImageFilter::SetFullyConnected "
27400
Set/Get whether the connected components are defined strictly by face
27401
connectivity or by face+edge+vertex connectivity. Default is
27402
FullyConnectedOff. For objects that are 1 pixel wide, use
27407
%feature("docstring") itk::simple::RegionalMaximaImageFilter::ToString "
27409
Print ourselves out
27413
%feature("docstring") itk::simple::RegionalMaximaImageFilter::~RegionalMaximaImageFilter "
27420
%feature("docstring") itk::simple::RegionalMinimaImageFilter "
27422
Produce a binary image where foreground is the regional minima of the
27426
Regional minima are flat zones surrounded by pixels of greater value.
27428
If the input image is constant, the entire image can be considered as
27429
a minima or not. The SetFlatIsMinima() method let the user choose which behavior to use.
27431
This class was contribtued to the Insight Journal by
27432
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
27433
de Jouy-en-Josas, France. https://hdl.handle.net/1926/153
27436
RegionalMaximaImageFilter
27438
ValuedRegionalMinimaImageFilter
27440
HConcaveImageFilter
27445
RegionalMinimaImageFilter
27447
itk::simple::RegionalMinima for the procedural interface
27449
itk::RegionalMinimaImageFilter for the Doxygen on the original ITK class.
27453
C++ includes: sitkRegionalMinimaImageFilter.h
27456
%feature("docstring") itk::simple::RegionalMinimaImageFilter::Execute "
27458
Execute the filter on the input image
27462
%feature("docstring") itk::simple::RegionalMinimaImageFilter::Execute "
27464
Execute the filter on the input image with the given parameters
27468
%feature("docstring") itk::simple::RegionalMinimaImageFilter::FlatIsMinimaOff "
27471
%feature("docstring") itk::simple::RegionalMinimaImageFilter::FlatIsMinimaOn "
27473
Set the value of FlatIsMinima to true or false respectfully.
27477
%feature("docstring") itk::simple::RegionalMinimaImageFilter::FullyConnectedOff "
27480
%feature("docstring") itk::simple::RegionalMinimaImageFilter::FullyConnectedOn "
27482
Set the value of FullyConnected to true or false respectfully.
27486
%feature("docstring") itk::simple::RegionalMinimaImageFilter::GetBackgroundValue "
27488
Set/Get the value used as \"background\" in the output image. Defaults
27489
to NumericTraits<PixelType>::NonpositiveMin() .
27493
%feature("docstring") itk::simple::RegionalMinimaImageFilter::GetFlatIsMinima "
27495
Set/Get wether a flat image must be considered as a minima or not.
27500
%feature("docstring") itk::simple::RegionalMinimaImageFilter::GetForegroundValue "
27502
Set/Get the value in the output image to consider as \"foreground\".
27503
Defaults to maximum value of PixelType.
27507
%feature("docstring") itk::simple::RegionalMinimaImageFilter::GetFullyConnected "
27509
Set/Get whether the connected components are defined strictly by face
27510
connectivity or by face+edge+vertex connectivity. Default is
27511
FullyConnectedOff. For objects that are 1 pixel wide, use
27516
%feature("docstring") itk::simple::RegionalMinimaImageFilter::GetName "
27522
%feature("docstring") itk::simple::RegionalMinimaImageFilter::RegionalMinimaImageFilter "
27524
Default Constructor that takes no arguments and initializes default
27529
%feature("docstring") itk::simple::RegionalMinimaImageFilter::SetBackgroundValue "
27531
Set/Get the value used as \"background\" in the output image. Defaults
27532
to NumericTraits<PixelType>::NonpositiveMin() .
27536
%feature("docstring") itk::simple::RegionalMinimaImageFilter::SetFlatIsMinima "
27538
Set/Get wether a flat image must be considered as a minima or not.
27543
%feature("docstring") itk::simple::RegionalMinimaImageFilter::SetForegroundValue "
27545
Set/Get the value in the output image to consider as \"foreground\".
27546
Defaults to maximum value of PixelType.
27550
%feature("docstring") itk::simple::RegionalMinimaImageFilter::SetFullyConnected "
27552
Set/Get whether the connected components are defined strictly by face
27553
connectivity or by face+edge+vertex connectivity. Default is
27554
FullyConnectedOff. For objects that are 1 pixel wide, use
27559
%feature("docstring") itk::simple::RegionalMinimaImageFilter::ToString "
27561
Print ourselves out
27565
%feature("docstring") itk::simple::RegionalMinimaImageFilter::~RegionalMinimaImageFilter "
27572
%feature("docstring") itk::simple::RelabelComponentImageFilter "
27574
Relabel the components in an image such that consecutive labels are
27578
RelabelComponentImageFilter remaps the labels associated with the objects in an image (as from
27579
the output of ConnectedComponentImageFilter ) such that the label numbers are consecutive with no gaps between
27580
the label numbers used. By default, the relabeling will also sort the
27581
labels based on the size of the object: the largest object will have
27582
label #1, the second largest will have label #2, etc. If two labels
27583
have the same size their initial order is kept. The sorting by size
27584
can be disabled using SetSortByObjectSize.
27586
Label #0 is assumed to be the background and is left unaltered by the
27589
RelabelComponentImageFilter is typically used on the output of the ConnectedComponentImageFilter for those applications that want to extract the largest object or the
27590
\"k\" largest objects. Any particular object can be extracted from the
27591
relabeled output using a BinaryThresholdImageFilter . A group of objects can be extracted from the relabled output using
27592
a ThresholdImageFilter .
27594
Once all the objects are relabeled, the application can query the
27595
number of objects and the size of each object. Object sizes are returned in a vector. The size of the background is not
27596
calculated. So the size of object #1 is GetSizeOfObjectsInPixels()
27597
[0], the size of object #2 is GetSizeOfObjectsInPixels() [1], etc.
27599
If user sets a minimum object size, all objects with fewer pixels than
27600
the minimum will be discarded, so that the number of objects reported
27601
will be only those remaining. The GetOriginalNumberOfObjects method
27602
can be called to find out how many objects were present before the
27603
small ones were discarded.
27605
RelabelComponentImageFilter can be run as an \"in place\" filter, where it will overwrite its
27606
output. The default is run out of place (or generate a separate
27607
output). \"In place\" operation can be controlled via methods in the
27608
superclass, InPlaceImageFilter::InPlaceOn() and
27609
InPlaceImageFilter::InPlaceOff() .
27613
ConnectedComponentImageFilter , BinaryThresholdImageFilter , ThresholdImageFilter
27618
Assign contiguous labels to connected regions of an image
27620
itk::simple::RelabelComponent for the procedural interface
27622
itk::RelabelComponentImageFilter for the Doxygen on the original ITK class.
27626
C++ includes: sitkRelabelComponentImageFilter.h
27629
%feature("docstring") itk::simple::RelabelComponentImageFilter::Execute "
27631
Execute the filter on the input image
27635
%feature("docstring") itk::simple::RelabelComponentImageFilter::Execute "
27637
Execute the filter on the input image with the given parameters
27641
%feature("docstring") itk::simple::RelabelComponentImageFilter::GetMinimumObjectSize "
27643
Get the caller-defined minimum size of an object in pixels. If the
27644
caller has not set the minimum, 0 will be returned, which is to be
27645
interpreted as meaning that no minimum exists, and all objects in the
27646
original label map will be passed through to the output.
27650
%feature("docstring") itk::simple::RelabelComponentImageFilter::GetName "
27656
%feature("docstring") itk::simple::RelabelComponentImageFilter::RelabelComponentImageFilter "
27658
Default Constructor that takes no arguments and initializes default
27663
%feature("docstring") itk::simple::RelabelComponentImageFilter::SetMinimumObjectSize "
27665
Set the minimum size in pixels for an object. All objects smaller than
27666
this size will be discarded and will not appear in the output label
27667
map. NumberOfObjects will count only the objects whose pixel counts
27668
are greater than or equal to the minimum size. Call
27669
GetOriginalNumberOfObjects to find out how many objects were present
27670
in the original label map.
27674
%feature("docstring") itk::simple::RelabelComponentImageFilter::ToString "
27676
Print ourselves out
27680
%feature("docstring") itk::simple::RelabelComponentImageFilter::~RelabelComponentImageFilter "
27687
%feature("docstring") itk::simple::RelabelLabelMapFilter "
27689
This filter relabels the LabelObjects; the new labels are arranged
27690
consecutively with consideration for the background value.
27693
This filter takes the LabelObjects from the input and reassigns them
27694
to the output by calling the PushLabelObject method, which by default,
27695
attempts to reorganize the labels consecutively. The user can assign
27696
an arbitrary value to the background; the filter will assign the
27697
labels consecutively by skipping the background value.
27699
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/1926/584 or http://www.insight-journal.org/browse/publication/176
27700
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
27701
de Jouy-en-Josas, France.
27704
ShapeLabelObject , RelabelComponentImageFilter
27706
itk::simple::RelabelLabelMapFilter for the procedural interface
27708
itk::RelabelLabelMapFilter for the Doxygen on the original ITK class.
27711
C++ includes: sitkRelabelLabelMapFilter.h
27714
%feature("docstring") itk::simple::RelabelLabelMapFilter::Execute "
27716
Execute the filter on the input image
27720
%feature("docstring") itk::simple::RelabelLabelMapFilter::Execute "
27722
Execute the filter on the input image with the given parameters
27726
%feature("docstring") itk::simple::RelabelLabelMapFilter::GetName "
27732
%feature("docstring") itk::simple::RelabelLabelMapFilter::GetReverseOrdering "
27735
%feature("docstring") itk::simple::RelabelLabelMapFilter::RelabelLabelMapFilter "
27737
Default Constructor that takes no arguments and initializes default
27742
%feature("docstring") itk::simple::RelabelLabelMapFilter::ReverseOrderingOff "
27745
%feature("docstring") itk::simple::RelabelLabelMapFilter::ReverseOrderingOn "
27747
Set the value of ReverseOrdering to true or false respectfully.
27751
%feature("docstring") itk::simple::RelabelLabelMapFilter::SetReverseOrdering "
27754
%feature("docstring") itk::simple::RelabelLabelMapFilter::ToString "
27756
Print ourselves out
27760
%feature("docstring") itk::simple::RelabelLabelMapFilter::~RelabelLabelMapFilter "
27767
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter "
27769
Threshold an image using the RenyiEntropy Threshold.
27772
This filter creates a binary thresholded image that separates an image
27773
into foreground and background components. The filter computes the
27774
threshold using the RenyiEntropyThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
27777
Richard Beare. Department of Medicine, Monash University, Melbourne,
27779
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
27780
de Jouy-en-Josas, France.
27782
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
27786
HistogramThresholdImageFilter
27788
itk::simple::RenyiEntropyThreshold for the procedural interface
27790
itk::RenyiEntropyThresholdImageFilter for the Doxygen on the original ITK class.
27793
C++ includes: sitkRenyiEntropyThresholdImageFilter.h
27796
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::Execute "
27798
Execute the filter on the input image
27802
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::Execute "
27805
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::Execute "
27807
Execute the filter on the input image with the given parameters
27811
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::Execute "
27814
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetInsideValue "
27816
Get the \"inside\" pixel value.
27820
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetMaskOutput "
27823
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetMaskValue "
27826
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetName "
27832
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetNumberOfHistogramBins "
27835
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetOutsideValue "
27837
Get the \"outside\" pixel value.
27841
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::GetThreshold "
27843
Get the computed threshold.
27846
This is a measurement. Its value is updated in the Execute methods, so
27847
the value will only be valid after an execution.
27851
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::MaskOutputOff "
27854
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::MaskOutputOn "
27856
Set the value of MaskOutput to true or false respectfully.
27860
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::RenyiEntropyThresholdImageFilter "
27862
Default Constructor that takes no arguments and initializes default
27867
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::SetInsideValue "
27869
Set the \"inside\" pixel value.
27873
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::SetMaskOutput "
27875
Do you want the output to be masked by the mask used in histogram
27876
construction. Only relevant if masking is in use.
27880
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::SetMaskValue "
27882
The value in the mask image, if used, indicating voxels that should be
27883
included. Default is the max of pixel type, as in the
27884
MaskedImageToHistogramFilter
27888
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::SetNumberOfHistogramBins "
27890
Set/Get the number of histogram bins.
27894
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::SetOutsideValue "
27896
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
27900
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::ToString "
27902
Print ourselves out
27906
%feature("docstring") itk::simple::RenyiEntropyThresholdImageFilter::~RenyiEntropyThresholdImageFilter "
27913
%feature("docstring") itk::simple::ResampleImageFilter "
27915
Resample an image via a coordinate transform.
27918
ResampleImageFilter resamples an existing image through some coordinate transform,
27919
interpolating via some image function. The class is templated over the
27920
types of the input and output images.
27922
Note that the choice of interpolator function can be important. This
27923
function is set via SetInterpolator() . The default is LinearInterpolateImageFunction <InputImageType, TInterpolatorPrecisionType>, which is reasonable for
27924
ordinary medical images. However, some synthetic images have pixels
27925
drawn from a finite prescribed set. An example would be a mask
27926
indicating the segmentation of a brain into a small number of tissue
27927
types. For such an image, one does not want to interpolate between
27928
different pixel values, and so NearestNeighborInterpolateImageFunction < InputImageType, TCoordRep > would be a better choice.
27930
If an sample is taken from outside the image domain, the default
27931
behavior is to use a default pixel value. If different behavior is
27932
desired, an extrapolator function can be set with SetExtrapolator() .
27934
Output information (spacing, size and direction) for the output image
27935
should be set. This information has the normal defaults of unit
27936
spacing, zero origin and identity direction. Optionally, the output
27937
information can be obtained from a reference image. If the reference
27938
image is provided and UseReferenceImage is On, then the spacing,
27939
origin and direction of the reference image will be used.
27941
Since this filter produces an image which is a different size than its
27942
input, it needs to override several of the methods defined in ProcessObject in order to properly manage the pipeline execution model. In
27943
particular, this filter overrides
27944
ProcessObject::GenerateInputRequestedRegion() and
27945
ProcessObject::GenerateOutputInformation() .
27947
This filter is implemented as a multithreaded filter. It provides a
27948
ThreadedGenerateData() method for its implementation.
27950
For multithreading, the TransformPoint method of the user-designated
27951
coordinate transform must be threadsafe.
27958
Upsampling an image
27960
Resample (stretch or compress) an image
27963
itk::ResampleImageFilter for the Doxygen on the original ITK class.
27966
C++ includes: sitkResampleImageFilter.h
27969
%feature("docstring") itk::simple::ResampleImageFilter::Execute "
27971
Execute the filter on the input image
27975
%feature("docstring") itk::simple::ResampleImageFilter::Execute "
27977
Execute the filter on the input image with the given parameters
27981
%feature("docstring") itk::simple::ResampleImageFilter::GetDefaultPixelValue "
27983
Get/Set the pixel value when a transformed pixel is outside of the
27984
image. The default default pixel value is 0.
27988
%feature("docstring") itk::simple::ResampleImageFilter::GetInterpolator "
27990
Get/Set the interpolator function. The default is LinearInterpolateImageFunction <InputImageType, TInterpolatorPrecisionType>. Some other options are NearestNeighborInterpolateImageFunction (useful for binary masks and other images with a small number of
27991
possible pixel values), and BSplineInterpolateImageFunction (which provides a higher order of interpolation).
27995
%feature("docstring") itk::simple::ResampleImageFilter::GetName "
28001
%feature("docstring") itk::simple::ResampleImageFilter::GetOutputDirection "
28003
Set the output direciton cosine matrix.
28007
%feature("docstring") itk::simple::ResampleImageFilter::GetOutputOrigin "
28009
Get the output image origin.
28013
%feature("docstring") itk::simple::ResampleImageFilter::GetOutputPixelType "
28015
Get the ouput pixel type.
28019
%feature("docstring") itk::simple::ResampleImageFilter::GetOutputSpacing "
28021
Get the output image spacing.
28025
%feature("docstring") itk::simple::ResampleImageFilter::GetSize "
28027
Get/Set the size of the output image.
28031
%feature("docstring") itk::simple::ResampleImageFilter::GetTransform "
28033
Get/Set the coordinate transformation. Set the coordinate transform to
28034
use for resampling. Note that this must be in physical coordinates and
28035
it is the output-to-input transform, NOT the input-to-output transform
28036
that you might naively expect. By default the filter uses an Identity
28037
transform. You must provide a different transform here, before
28038
attempting to run the filter, if you do not want to use the default
28039
Identity transform.
28043
%feature("docstring") itk::simple::ResampleImageFilter::ResampleImageFilter "
28045
Default Constructor that takes no arguments and initializes default
28050
%feature("docstring") itk::simple::ResampleImageFilter::SetDefaultPixelValue "
28052
Get/Set the pixel value when a transformed pixel is outside of the
28053
image. The default default pixel value is 0.
28057
%feature("docstring") itk::simple::ResampleImageFilter::SetInterpolator "
28059
Get/Set the interpolator function. The default is LinearInterpolateImageFunction <InputImageType, TInterpolatorPrecisionType>. Some other options are NearestNeighborInterpolateImageFunction (useful for binary masks and other images with a small number of
28060
possible pixel values), and BSplineInterpolateImageFunction (which provides a higher order of interpolation).
28064
%feature("docstring") itk::simple::ResampleImageFilter::SetOutputDirection "
28066
Set the output direciton cosine matrix.
28070
%feature("docstring") itk::simple::ResampleImageFilter::SetOutputOrigin "
28072
Set the output image origin.
28076
%feature("docstring") itk::simple::ResampleImageFilter::SetOutputPixelType "
28078
Set the output pixel type, if sitkUnknown then the input type is used.
28082
%feature("docstring") itk::simple::ResampleImageFilter::SetOutputSpacing "
28084
Set the output image spacing.
28088
%feature("docstring") itk::simple::ResampleImageFilter::SetReferenceImage "
28090
This methods sets the output size, origin, spacing and direction to
28091
that of the provided image
28095
%feature("docstring") itk::simple::ResampleImageFilter::SetSize "
28097
Get/Set the size of the output image.
28101
%feature("docstring") itk::simple::ResampleImageFilter::SetTransform "
28103
Get/Set the coordinate transformation. Set the coordinate transform to
28104
use for resampling. Note that this must be in physical coordinates and
28105
it is the output-to-input transform, NOT the input-to-output transform
28106
that you might naively expect. By default the filter uses an Identity
28107
transform. You must provide a different transform here, before
28108
attempting to run the filter, if you do not want to use the default
28109
Identity transform.
28113
%feature("docstring") itk::simple::ResampleImageFilter::ToString "
28115
Print ourselves out
28119
%feature("docstring") itk::simple::ResampleImageFilter::~ResampleImageFilter "
28126
%feature("docstring") itk::simple::RescaleIntensityImageFilter "
28128
Applies a linear transformation to the intensity levels of the input Image .
28131
RescaleIntensityImageFilter applies pixel-wise a linear transformation to the intensity values of
28132
input image pixels. The linear transformation is defined by the user
28133
in terms of the minimum and maximum values that the output image
28136
The following equation gives the mapping of the intensity values
28139
\\\\[ outputPixel = ( inputPixel - inputMin) \\\\cdot
28140
\\\\frac{(outputMax - outputMin )}{(inputMax - inputMin)} + outputMin
28142
All computations are performed in the precision of the input pixel's
28143
RealType. Before assigning the computed value to the output pixel.
28145
NOTE: In this filter the minimum and maximum values of the input image
28146
are computed internally using the MinimumMaximumImageCalculator . Users are not supposed to set those values in this filter. If you
28147
need a filter where you can set the minimum and maximum values of the
28148
input, please use the IntensityWindowingImageFilter . If you want a filter that can use a user-defined linear
28149
transformation for the intensity, then please use the ShiftScaleImageFilter .
28153
IntensityWindowingImageFilter
28158
Rescale the intensity values of an image to a specified range
28160
itk::simple::RescaleIntensity for the procedural interface
28162
itk::RescaleIntensityImageFilter for the Doxygen on the original ITK class.
28166
C++ includes: sitkRescaleIntensityImageFilter.h
28169
%feature("docstring") itk::simple::RescaleIntensityImageFilter::Execute "
28171
Execute the filter on the input image
28175
%feature("docstring") itk::simple::RescaleIntensityImageFilter::Execute "
28177
Execute the filter on the input image with the given parameters
28181
%feature("docstring") itk::simple::RescaleIntensityImageFilter::GetName "
28187
%feature("docstring") itk::simple::RescaleIntensityImageFilter::GetOutputMaximum "
28190
%feature("docstring") itk::simple::RescaleIntensityImageFilter::GetOutputMinimum "
28193
%feature("docstring") itk::simple::RescaleIntensityImageFilter::RescaleIntensityImageFilter "
28195
Default Constructor that takes no arguments and initializes default
28200
%feature("docstring") itk::simple::RescaleIntensityImageFilter::SetOutputMaximum "
28203
%feature("docstring") itk::simple::RescaleIntensityImageFilter::SetOutputMinimum "
28206
%feature("docstring") itk::simple::RescaleIntensityImageFilter::ToString "
28208
Print ourselves out
28212
%feature("docstring") itk::simple::RescaleIntensityImageFilter::~RescaleIntensityImageFilter "
28219
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter "
28221
Deconvolve an image using the Richardson-Lucy deconvolution algorithm.
28224
This filter implements the Richardson-Lucy deconvolution algorithm as
28225
defined in Bertero M and Boccacci P, \"Introduction to Inverse
28226
Problems in Imaging\", 1998. The algorithm assumes that the input
28227
image has been formed by a linear shift-invariant system with a known
28230
The Richardson-Lucy algorithm assumes that noise in the image follows
28231
a Poisson distribution and that the distribution for each pixel is
28232
independent of the other pixels.
28234
This code was adapted from the Insight Journal contribution:
28236
\"Deconvolution: infrastructure and reference algorithms\" by Gaetan
28237
Lehmann https://hdl.handle.net/10380/3207
28240
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
28241
de Jouy-en-Josas, France
28242
Cory Quammen, The University of North Carolina at Chapel Hill
28246
IterativeDeconvolutionImageFilter
28248
LandweberDeconvolutionImageFilter
28250
ProjectedLandweberDeconvolutionImageFilter
28252
itk::simple::RichardsonLucyDeconvolution for the procedural interface
28254
itk::RichardsonLucyDeconvolutionImageFilter for the Doxygen on the original ITK class.
28257
C++ includes: sitkRichardsonLucyDeconvolutionImageFilter.h
28260
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::Execute "
28262
Execute the filter on the input images
28266
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::Execute "
28268
Execute the filter on the input images with the given parameters
28272
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::GetBoundaryCondition "
28275
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::GetName "
28281
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::GetNormalize "
28284
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::GetNumberOfIterations "
28286
Get the number of iterations.
28290
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::GetOutputRegionMode "
28293
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::NormalizeOff "
28296
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::NormalizeOn "
28298
Set the value of Normalize to true or false respectfully.
28302
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::RichardsonLucyDeconvolutionImageFilter "
28304
Default Constructor that takes no arguments and initializes default
28309
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::SetBoundaryCondition "
28312
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::SetNormalize "
28314
Normalize the output image by the sum of the kernel components
28318
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::SetNumberOfIterations "
28320
Set the number of iterations.
28324
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::SetOutputRegionMode "
28327
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::ToString "
28329
Print ourselves out
28333
%feature("docstring") itk::simple::RichardsonLucyDeconvolutionImageFilter::~RichardsonLucyDeconvolutionImageFilter "
28340
%feature("docstring") itk::simple::STAPLEImageFilter "
28342
The STAPLE filter implements the Simultaneous Truth and Performance
28343
Level Estimation algorithm for generating ground truth volumes from a
28344
set of binary expert segmentations.
28347
The STAPLE algorithm treats segmentation as a pixelwise
28348
classification, which leads to an averaging scheme that accounts for
28349
systematic biases in the behavior of experts in order to generate a
28350
fuzzy ground truth volume and simultaneous accuracy assessment of each
28351
expert. The ground truth volumes produced by this filter are floating
28352
point volumes of values between zero and one that indicate probability
28353
of each pixel being in the object targeted by the segmentation.
28355
The STAPLE algorithm is described in
28357
S. Warfield, K. Zou, W. Wells, \"Validation of image segmentation and
28358
expert quality with an expectation-maximization algorithm\" in MICCAI
28359
2002: Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer-Verlag,
28360
Heidelberg, Germany, 2002, pp. 298-306
28363
Input volumes to the STAPLE filter must be binary segmentations of an
28364
image, that is, there must be a single foreground value that
28365
represents positively classified pixels (pixels that are considered to
28366
belong inside the segmentation). Any number of background pixel values
28367
may be present in the input images. You can, for example, input
28368
volumes with many different labels as long as the structure you are
28369
interested in creating ground truth for is consistently labeled among
28370
all input volumes. Pixel type of the input volumes does not matter.
28371
Specify the label value for positively classified pixels using
28372
SetForegroundValue. All other labels will be considered to be
28373
negatively classified pixels (background).
28374
Input volumes must all contain the same size RequestedRegions.
28377
The STAPLE filter produces a single output volume with a range of
28378
floating point values from zero to one. IT IS VERY IMPORTANT TO
28379
INSTANTIATE THIS FILTER WITH A FLOATING POINT OUTPUT TYPE (floats or
28380
doubles). You may threshold the output above some probability
28381
threshold if you wish to produce a binary ground truth.
28383
The STAPLE algorithm requires a number of inputs. You may specify any
28384
number of input volumes using the SetInput(i, p_i) method, where i
28385
ranges from zero to N-1, N is the total number of input segmentations,
28386
and p_i is the SmartPointer to the i-th segmentation.
28387
The SetConfidenceWeight parameter is a modifier for the prior
28388
probability that any pixel would be classified as inside the target
28389
object. This implementation of the STAPLE algorithm automatically
28390
calculates prior positive classification probability as the average
28391
fraction of the image volume filled by the target object in each input
28392
segmentation. The ConfidenceWeight parameter allows for scaling the of
28393
this default prior probability: if g_t is the prior probability that a
28394
pixel would be classified inside the target object, then g_t is set to
28395
g_t * ConfidenceWeight before iterating on the solution. In general
28396
ConfidenceWeight should be left to the default of 1.0.
28398
You must provide a foreground value using SetForegroundValue that the
28399
STAPLE algorithm will use to identify positively classified pixels in
28400
the the input images. All other values in the image will be treated as
28401
background values. For example, if your input segmentations consist of
28402
1's everywhere inside the segmented region, then use
28403
SetForegroundValue(1).
28405
The STAPLE algorithm is an iterative E-M algorithm and will converge
28406
on a solution after some number of iterations that cannot be known a
28407
priori. After updating the filter, the total elapsed iterations taken
28408
to converge on the solution can be queried through GetElapsedIterations() . You may also specify a MaximumNumberOfIterations, after which the
28409
algorithm will stop iterating regardless of whether or not it has
28410
converged. This implementation of the STAPLE algorithm will find the
28411
solution to within seven digits of precision unless it is stopped
28414
Once updated, the Sensitivity (true positive fraction, q) and
28415
Specificity (true negative fraction, q) for each expert input volume
28416
can be queried using GetSensitivity(i) and GetSpecificity(i), where i
28417
is the i-th input volume.
28419
REQUIRED PARAMETERS
28420
The only required parameters for this filter are the ForegroundValue
28421
and the input volumes. All other parameters may be safely left to
28422
their default values. Please see the paper cited above for more
28423
information on the STAPLE algorithm and its parameters. A proper
28424
understanding of the algorithm is important for interpreting the
28425
results that it produces.
28427
This filter invokes IterationEvent() at each iteration of the E-M
28428
algorithm. Setting the AbortGenerateData() flag will cause the
28429
algorithm to halt after the current iteration and produce results just
28430
as if it had converged. The algorithm makes no attempt to report its
28431
progress since the number of iterations needed cannot be known in
28435
itk::simple::STAPLE for the procedural interface
28438
C++ includes: sitkSTAPLEImageFilter.h
28441
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28443
Execute the filter on the input images
28447
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28450
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28453
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28456
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28459
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28462
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28464
Execute the filter on the input images with the given parameters
28468
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28471
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28474
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28477
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28480
%feature("docstring") itk::simple::STAPLEImageFilter::Execute "
28483
%feature("docstring") itk::simple::STAPLEImageFilter::GetConfidenceWeight "
28485
Scales the estimated prior probability that a pixel will be inside the
28486
targeted object of segmentation. The default prior probability g_t is
28487
calculated automatically as the average fraction of positively
28488
classified pixels to the total size of the volume (across all input
28489
volumes). ConfidenceWeight will scale this default value as g_t = g_t
28490
* ConfidenceWeight. In general, ConfidenceWeight should be left to the
28495
%feature("docstring") itk::simple::STAPLEImageFilter::GetElapsedIterations "
28497
Get the number of elapsed iterations of the iterative E-M algorithm.
28499
This is a measurement. Its value is updated in the Execute methods, so
28500
the value will only be valid after an execution.
28504
%feature("docstring") itk::simple::STAPLEImageFilter::GetForegroundValue "
28506
Set get the binary ON value of the input image.
28510
%feature("docstring") itk::simple::STAPLEImageFilter::GetMaximumIterations "
28512
Set/Get the maximum number of iterations after which the STAPLE
28513
algorithm will be considered to have converged. In general this SHOULD
28514
NOT be set and the algorithm should be allowed to converge on its own.
28518
%feature("docstring") itk::simple::STAPLEImageFilter::GetName "
28524
%feature("docstring") itk::simple::STAPLEImageFilter::GetSensitivity "
28526
After the filter is updated, this method returns a std::vector<double>
28527
of all Sensitivity (true positive fraction, p) values for the expert
28530
This is a measurement. Its value is updated in the Execute methods, so
28531
the value will only be valid after an execution.
28535
%feature("docstring") itk::simple::STAPLEImageFilter::GetSpecificity "
28537
After the filter is updated, this method returns the Specificity (true
28538
negative fraction, q) value for the i-th expert input volume.
28541
This is a measurement. Its value is updated in the Execute methods, so
28542
the value will only be valid after an execution.
28546
%feature("docstring") itk::simple::STAPLEImageFilter::SetConfidenceWeight "
28548
Scales the estimated prior probability that a pixel will be inside the
28549
targeted object of segmentation. The default prior probability g_t is
28550
calculated automatically as the average fraction of positively
28551
classified pixels to the total size of the volume (across all input
28552
volumes). ConfidenceWeight will scale this default value as g_t = g_t
28553
* ConfidenceWeight. In general, ConfidenceWeight should be left to the
28558
%feature("docstring") itk::simple::STAPLEImageFilter::SetForegroundValue "
28560
Set get the binary ON value of the input image.
28564
%feature("docstring") itk::simple::STAPLEImageFilter::SetMaximumIterations "
28566
Set/Get the maximum number of iterations after which the STAPLE
28567
algorithm will be considered to have converged. In general this SHOULD
28568
NOT be set and the algorithm should be allowed to converge on its own.
28572
%feature("docstring") itk::simple::STAPLEImageFilter::STAPLEImageFilter "
28574
Default Constructor that takes no arguments and initializes default
28579
%feature("docstring") itk::simple::STAPLEImageFilter::ToString "
28581
Print ourselves out
28585
%feature("docstring") itk::simple::STAPLEImageFilter::~STAPLEImageFilter "
28592
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter "
28594
Alter an image with fixed value impulse noise, often called salt and
28598
Pixel alteration occurs at a user defined probability. Salt and pepper
28599
pixel are equally distributed.
28603
This code was contributed in the Insight Journal paper \"Noise
28604
Simulation\". https://hdl.handle.net/10380/3158
28606
itk::simple::SaltAndPepperNoise for the procedural interface
28608
itk::SaltAndPepperNoiseImageFilter for the Doxygen on the original ITK class.
28611
C++ includes: sitkSaltAndPepperNoiseImageFilter.h
28614
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::Execute "
28616
Execute the filter on the input image
28620
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::Execute "
28622
Execute the filter on the input image with the given parameters
28626
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::GetName "
28632
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::GetProbability "
28635
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::GetSeed "
28638
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::SaltAndPepperNoiseImageFilter "
28640
Default Constructor that takes no arguments and initializes default
28645
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::SetProbability "
28648
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::SetSeed "
28651
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::ToString "
28653
Print ourselves out
28657
%feature("docstring") itk::simple::SaltAndPepperNoiseImageFilter::~SaltAndPepperNoiseImageFilter "
28664
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter "
28666
Dense implementation of the Chan and Vese multiphase level set image
28670
This code was adapted from the paper: \"An active contour model
28671
without edges\" T. Chan and L. Vese. In Scale-Space Theories in
28672
Computer Vision, pages 141-151, 1999.
28675
Mosaliganti K., Smith B., Gelas A., Gouaillard A., Megason S.
28676
This code was taken from the Insight Journal paper: \"Cell Tracking
28677
using Coupled Active Surfaces for Nuclei and Membranes\" http://www.insight-journal.org/browse/publication/642 https://hdl.handle.net/10380/3055
28679
That is based on the papers: \"Level Set Segmentation: Active Contours
28680
without edge\" http://www.insight-journal.org/browse/publication/322 https://hdl.handle.net/1926/1532
28684
\"Level set segmentation using coupled active surfaces\" http://www.insight-journal.org/browse/publication/323 https://hdl.handle.net/1926/1533
28690
Single-phase Chan And Vese Dense Field Level Set Segmentation
28692
itk::simple::ScalarChanAndVeseDenseLevelSet for the procedural interface
28694
itk::ScalarChanAndVeseDenseLevelSetImageFilter for the Doxygen on the original ITK class.
28698
C++ includes: sitkScalarChanAndVeseDenseLevelSetImageFilter.h
28701
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::Execute "
28703
Execute the filter on the input images
28707
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::Execute "
28709
Execute the filter on the input images with the given parameters
28713
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetAreaWeight "
28716
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetCurvatureWeight "
28719
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetElapsedIterations "
28721
Number of iterations run.
28724
This is a measurement. Its value is updated in the Execute methods, so
28725
the value will only be valid after an execution.
28729
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetEpsilon "
28732
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetHeavisideStepFunction "
28735
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetLambda1 "
28738
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetLambda2 "
28741
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetMaximumRMSError "
28744
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetName "
28750
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetNumberOfIterations "
28753
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetReinitializationSmoothingWeight "
28756
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetRMSChange "
28758
The Root Mean Square of the levelset upon termination.
28761
This is a measurement. Its value is updated in the Execute methods, so
28762
the value will only be valid after an execution.
28766
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetUseImageSpacing "
28768
Use the image spacing information in calculations. Use this option if
28769
you want derivatives in physical space. Default is UseImageSpacingOn.
28773
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetVolume "
28776
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::GetVolumeMatchingWeight "
28779
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::ScalarChanAndVeseDenseLevelSetImageFilter "
28781
Default Constructor that takes no arguments and initializes default
28786
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetAreaWeight "
28789
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetCurvatureWeight "
28792
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetEpsilon "
28795
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetHeavisideStepFunction "
28798
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetLambda1 "
28801
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetLambda2 "
28804
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetMaximumRMSError "
28807
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetNumberOfIterations "
28810
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetReinitializationSmoothingWeight "
28813
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetUseImageSpacing "
28815
Use the image spacing information in calculations. Use this option if
28816
you want derivatives in physical space. Default is UseImageSpacingOn.
28820
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetVolume "
28823
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::SetVolumeMatchingWeight "
28826
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::ToString "
28828
Print ourselves out
28832
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::UseImageSpacingOff "
28835
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::UseImageSpacingOn "
28837
Set the value of UseImageSpacing to true or false respectfully.
28841
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter::~ScalarChanAndVeseDenseLevelSetImageFilter "
28848
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter "
28850
A connected components filter that labels the objects in an arbitrary
28851
image. Two pixels are similar if they are within threshold of each
28852
other. Uses ConnectedComponentFunctorImageFilter .
28859
Label connected components in a grayscale image
28861
itk::simple::ScalarConnectedComponent for the procedural interface
28863
itk::ScalarConnectedComponentImageFilter for the Doxygen on the original ITK class.
28867
C++ includes: sitkScalarConnectedComponentImageFilter.h
28870
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::Execute "
28872
Execute the filter on the input image
28876
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::Execute "
28878
Execute the filter on the input image with the given parameters
28882
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::FullyConnectedOff "
28885
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::FullyConnectedOn "
28887
Set the value of FullyConnected to true or false respectfully.
28891
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::GetDistanceThreshold "
28894
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::GetFullyConnected "
28897
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::GetName "
28903
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::ScalarConnectedComponentImageFilter "
28905
Default Constructor that takes no arguments and initializes default
28910
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::SetDistanceThreshold "
28913
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::SetFullyConnected "
28916
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::ToString "
28918
Print ourselves out
28922
%feature("docstring") itk::simple::ScalarConnectedComponentImageFilter::~ScalarConnectedComponentImageFilter "
28929
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter "
28931
Classifies the intensity values of a scalar image using the K-Means
28935
Given an input image with scalar values, it uses the K-Means
28936
statistical classifier in order to define labels for every pixel in
28937
the image. The filter is templated over the type of the input image.
28938
The output image is predefined as having the same dimension of the
28939
input image and pixel type unsigned char, under the assumption that
28940
the classifier will generate less than 256 classes.
28942
You may want to look also at the RelabelImageFilter that may be used
28943
as a postprocessing stage, in particular if you are interested in
28944
ordering the labels by their relative size in number of pixels.
28950
ImageKmeansModelEstimator
28952
KdTreeBasedKmeansEstimator, WeightedCentroidKdTreeGenerator, KdTree
28959
Cluster the pixels in a greyscale image
28961
itk::simple::ScalarImageKmeans for the procedural interface
28963
itk::ScalarImageKmeansImageFilter for the Doxygen on the original ITK class.
28967
C++ includes: sitkScalarImageKmeansImageFilter.h
28970
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::Execute "
28972
Execute the filter on the input image
28976
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::Execute "
28978
Execute the filter on the input image with the given parameters
28982
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::GetClassWithInitialMean "
28985
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::GetFinalMeans "
28987
Return the array of Means found after the classification.
28989
This is a measurement. Its value is updated in the Execute methods, so
28990
the value will only be valid after an execution.
28994
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::GetName "
29000
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::GetUseNonContiguousLabels "
29002
Set/Get the UseNonContiguousLabels flag. When this is set to false the
29003
labels are numbered contiguously, like in {0,1,3..N}. When the flag is
29004
set to true, the labels are selected in order to span the dynamic
29005
range of the output image. This last option is useful when the output
29006
image is intended only for display. The default value is false.
29010
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::ScalarImageKmeansImageFilter "
29012
Default Constructor that takes no arguments and initializes default
29017
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::SetClassWithInitialMean "
29020
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::SetUseNonContiguousLabels "
29022
Set/Get the UseNonContiguousLabels flag. When this is set to false the
29023
labels are numbered contiguously, like in {0,1,3..N}. When the flag is
29024
set to true, the labels are selected in order to span the dynamic
29025
range of the output image. This last option is useful when the output
29026
image is intended only for display. The default value is false.
29030
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::ToString "
29032
Print ourselves out
29036
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::UseNonContiguousLabelsOff "
29039
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::UseNonContiguousLabelsOn "
29041
Set the value of UseNonContiguousLabels to true or false respectfully.
29045
%feature("docstring") itk::simple::ScalarImageKmeansImageFilter::~ScalarImageKmeansImageFilter "
29052
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter "
29054
Implements pixel-wise intensity->rgb mapping operation on one image.
29057
This class is parameterized over the type of the input image and the
29058
type of the output image.
29060
The input image's scalar pixel values are mapped into a color map. The
29061
color map is specified by passing the SetColormap function one of the
29062
predefined maps. The following selects the \"Hot\" colormap:
29064
You can also specify a custom color map. This is done by creating a
29065
CustomColormapFunction, and then creating lists of values for the red,
29066
green, and blue channel. An example of setting the red channel of a
29067
colormap with only 2 colors is given below. The blue and green
29068
channels should be specified in the same manner.
29071
The range of values present in the input image is the range that is
29072
mapped to the entire range of colors.
29074
This code was contributed in the Insight Journal paper: \"Meeting Andy
29075
Warhol Somewhere Over the Rainbow: RGB Colormapping and ITK\" by
29076
Tustison N., Zhang H., Lehmann G., Yushkevich P., Gee J. https://hdl.handle.net/1926/1452 http://www.insight-journal.org/browse/publication/285
29080
BinaryFunctionImageFilter TernaryFunctionImageFilter
29085
Apply a color map to an image
29087
itk::simple::ScalarToRGBColormap for the procedural interface
29089
itk::ScalarToRGBColormapImageFilter for the Doxygen on the original ITK class.
29093
C++ includes: sitkScalarToRGBColormapImageFilter.h
29096
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::Execute "
29098
Execute the filter on the input image
29102
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::Execute "
29104
Execute the filter on the input image with the given parameters
29108
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::GetColormap "
29110
Set/Get the colormap object.
29114
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::GetName "
29120
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::GetUseInputImageExtremaForScaling "
29122
Set/Get UseInputImageExtremaForScaling. If true, the colormap uses the
29123
min and max values from the image to scale appropriately. Otherwise,
29124
these values can be set in the colormap manually.
29128
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::ScalarToRGBColormapImageFilter "
29130
Default Constructor that takes no arguments and initializes default
29135
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::SetColormap "
29138
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::SetUseInputImageExtremaForScaling "
29140
Set/Get UseInputImageExtremaForScaling. If true, the colormap uses the
29141
min and max values from the image to scale appropriately. Otherwise,
29142
these values can be set in the colormap manually.
29146
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::ToString "
29148
Print ourselves out
29152
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::UseInputImageExtremaForScalingOff "
29155
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::UseInputImageExtremaForScalingOn "
29157
Set the value of UseInputImageExtremaForScaling to true or false
29162
%feature("docstring") itk::simple::ScalarToRGBColormapImageFilter::~ScalarToRGBColormapImageFilter "
29169
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform "
29171
A over parameterized 3D Affine transform composed of the addition of a
29172
versor rotation matrix, a scale matrix and a skew matrix around a
29173
fixed center with translation.
29178
itk::ScaleSkewVersor3DTransform
29181
C++ includes: sitkScaleSkewVersor3DTransform.h
29184
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetCenter "
29187
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetMatrix "
29190
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetName "
29196
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetScale "
29199
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetSkew "
29202
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetTranslation "
29205
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::GetVersor "
29208
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::ScaleSkewVersor3DTransform "
29211
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::ScaleSkewVersor3DTransform "
29214
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::ScaleSkewVersor3DTransform "
29217
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::ScaleSkewVersor3DTransform "
29220
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::ScaleSkewVersor3DTransform "
29223
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetCenter "
29229
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetRotation "
29235
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetRotation "
29238
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetScale "
29241
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetSkew "
29244
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::SetTranslation "
29247
%feature("docstring") itk::simple::ScaleSkewVersor3DTransform::Translate "
29254
%feature("docstring") itk::simple::ScaleTransform "
29256
A 2D or 3D anisotropic scale of coordinate space around a fixed
29262
itk::ScaleTransform
29265
C++ includes: sitkScaleTransform.h
29268
%feature("docstring") itk::simple::ScaleTransform::GetCenter "
29271
%feature("docstring") itk::simple::ScaleTransform::GetMatrix "
29277
%feature("docstring") itk::simple::ScaleTransform::GetName "
29283
%feature("docstring") itk::simple::ScaleTransform::GetScale "
29286
%feature("docstring") itk::simple::ScaleTransform::ScaleTransform "
29289
%feature("docstring") itk::simple::ScaleTransform::ScaleTransform "
29292
%feature("docstring") itk::simple::ScaleTransform::ScaleTransform "
29295
%feature("docstring") itk::simple::ScaleTransform::SetCenter "
29301
%feature("docstring") itk::simple::ScaleTransform::SetScale "
29305
%feature("docstring") itk::simple::ScaleVersor3DTransform "
29307
A parameterized 3D transform composed of the addition of a versor
29308
rotation matrix and a scale matrix around a fixed center with
29314
itk::ScaleVersor3DTransform
29317
C++ includes: sitkScaleVersor3DTransform.h
29320
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetCenter "
29323
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetMatrix "
29326
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetName "
29332
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetScale "
29335
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetTranslation "
29338
%feature("docstring") itk::simple::ScaleVersor3DTransform::GetVersor "
29341
%feature("docstring") itk::simple::ScaleVersor3DTransform::ScaleVersor3DTransform "
29344
%feature("docstring") itk::simple::ScaleVersor3DTransform::ScaleVersor3DTransform "
29347
%feature("docstring") itk::simple::ScaleVersor3DTransform::ScaleVersor3DTransform "
29350
%feature("docstring") itk::simple::ScaleVersor3DTransform::ScaleVersor3DTransform "
29353
%feature("docstring") itk::simple::ScaleVersor3DTransform::ScaleVersor3DTransform "
29356
%feature("docstring") itk::simple::ScaleVersor3DTransform::SetCenter "
29362
%feature("docstring") itk::simple::ScaleVersor3DTransform::SetRotation "
29368
%feature("docstring") itk::simple::ScaleVersor3DTransform::SetRotation "
29371
%feature("docstring") itk::simple::ScaleVersor3DTransform::SetScale "
29374
%feature("docstring") itk::simple::ScaleVersor3DTransform::SetTranslation "
29377
%feature("docstring") itk::simple::ScaleVersor3DTransform::Translate "
29384
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter "
29386
Threshold an image using the Shanbhag Threshold.
29389
This filter creates a binary thresholded image that separates an image
29390
into foreground and background components. The filter computes the
29391
threshold using the ShanbhagThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
29394
Richard Beare. Department of Medicine, Monash University, Melbourne,
29396
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
29397
de Jouy-en-Josas, France.
29399
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
29403
HistogramThresholdImageFilter
29405
itk::simple::ShanbhagThreshold for the procedural interface
29407
itk::ShanbhagThresholdImageFilter for the Doxygen on the original ITK class.
29410
C++ includes: sitkShanbhagThresholdImageFilter.h
29413
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::Execute "
29415
Execute the filter on the input image
29419
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::Execute "
29422
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::Execute "
29424
Execute the filter on the input image with the given parameters
29428
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::Execute "
29431
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetInsideValue "
29433
Get the \"inside\" pixel value.
29437
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetMaskOutput "
29440
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetMaskValue "
29443
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetName "
29449
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetNumberOfHistogramBins "
29452
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetOutsideValue "
29454
Get the \"outside\" pixel value.
29458
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::GetThreshold "
29460
Get the computed threshold.
29463
This is a measurement. Its value is updated in the Execute methods, so
29464
the value will only be valid after an execution.
29468
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::MaskOutputOff "
29471
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::MaskOutputOn "
29473
Set the value of MaskOutput to true or false respectfully.
29477
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::SetInsideValue "
29479
Set the \"inside\" pixel value.
29483
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::SetMaskOutput "
29485
Do you want the output to be masked by the mask used in histogram
29486
construction. Only relevant if masking is in use.
29490
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::SetMaskValue "
29492
The value in the mask image, if used, indicating voxels that should be
29493
included. Default is the max of pixel type, as in the
29494
MaskedImageToHistogramFilter
29498
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::SetNumberOfHistogramBins "
29500
Set/Get the number of histogram bins.
29504
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::SetOutsideValue "
29506
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
29510
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::ShanbhagThresholdImageFilter "
29512
Default Constructor that takes no arguments and initializes default
29517
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::ToString "
29519
Print ourselves out
29523
%feature("docstring") itk::simple::ShanbhagThresholdImageFilter::~ShanbhagThresholdImageFilter "
29530
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter "
29532
Segments structures in images based on a user supplied edge potential
29537
The SegmentationLevelSetImageFilter class and the ShapeDetectionLevelSetFunction class contain additional information necessary to gain full
29538
understanding of how to use this filter.
29540
This class is a level set method segmentation filter. An initial
29541
contour is propagated outwards (or inwards) until it ''sticks'' to the
29542
shape boundaries. This is done by using a level set speed function
29543
based on a user supplied edge potential map. This approach for
29544
segmentation follows that of Malladi et al (1995).
29546
This filter requires two inputs. The first input is a initial level
29547
set. The initial level set is a real image which contains the initial
29548
contour/surface as the zero level set. For example, a signed distance
29549
function from the initial contour/surface is typically used. Note that
29550
for this algorithm the initial contour has to be wholly within (or
29551
wholly outside) the structure to be segmented.
29553
The second input is the feature image. For this filter, this is the
29554
edge potential map. General characteristics of an edge potential map
29555
is that it has values close to zero in regions near the edges and
29556
values close to one inside the shape itself. Typically, the edge
29557
potential map is compute from the image gradient, for example:
29558
\\\\[ g(I) = 1 / ( 1 + | (\\\\nabla * G)(I)| ) \\\\] \\\\[ g(I) = \\\\exp^{-|(\\\\nabla * G)(I)|} \\\\]
29560
where $ I $ is image intensity and $ (\\\\nabla * G) $ is the derivative of Gaussian operator.
29563
See SegmentationLevelSetImageFilter and SparseFieldLevelSetImageFilter for more information on Inputs.
29565
The PropagationScaling parameter can be used to switch from
29566
propagation outwards (POSITIVE scaling parameter) versus propagating
29567
inwards (NEGATIVE scaling parameter).
29568
The smoothness of the resulting contour/surface can be adjusted using
29569
a combination of PropagationScaling and CurvatureScaling parameters.
29570
The larger the CurvatureScaling parameter, the smoother the resulting
29571
contour. The CurvatureScaling parameter should be non-negative for
29572
proper operation of this algorithm. To follow the implementation in
29573
Malladi et al paper, set the PropagtionScaling to $\\\\pm 1.0$ and CurvatureScaling to $ \\\\epsilon $ .
29575
Note that there is no advection term for this filter. Setting the
29576
advection scaling will have no effect.
29579
The filter outputs a single, scalar, real-valued image. Negative
29580
values in the output image represent the inside of the segmentated
29581
region and positive values in the image represent the outside of the
29582
segmented region. The zero crossings of the image correspond to the
29583
position of the propagating front.
29585
See SparseFieldLevelSetImageFilter and SegmentationLevelSetImageFilter for more information.
29588
\"Shape Modeling with Front Propagation: A Level Set Approach\", R.
29589
Malladi, J. A. Sethian and B. C. Vermuri. IEEE Trans. on Pattern
29590
Analysis and Machine Intelligence, Vol 17, No. 2, pp 158-174, February
29594
SegmentationLevelSetImageFilter
29596
ShapeDetectionLevelSetFunction
29598
SparseFieldLevelSetImageFilter
29600
itk::simple::ShapeDetectionLevelSet for the procedural interface
29602
itk::ShapeDetectionLevelSetImageFilter for the Doxygen on the original ITK class.
29605
C++ includes: sitkShapeDetectionLevelSetImageFilter.h
29608
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::Execute "
29610
Execute the filter on the input images
29614
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::Execute "
29616
Execute the filter on the input images with the given parameters
29620
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetCurvatureScaling "
29623
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetElapsedIterations "
29625
Number of iterations run.
29628
This is a measurement. Its value is updated in the Execute methods, so
29629
the value will only be valid after an execution.
29633
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetMaximumRMSError "
29636
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetName "
29642
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetNumberOfIterations "
29645
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetPropagationScaling "
29648
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetReverseExpansionDirection "
29651
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::GetRMSChange "
29653
The Root Mean Square of the levelset upon termination.
29656
This is a measurement. Its value is updated in the Execute methods, so
29657
the value will only be valid after an execution.
29661
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::ReverseExpansionDirectionOff "
29664
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::ReverseExpansionDirectionOn "
29666
Set the value of ReverseExpansionDirection to true or false
29671
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::SetCurvatureScaling "
29674
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::SetMaximumRMSError "
29677
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::SetNumberOfIterations "
29680
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::SetPropagationScaling "
29683
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::SetReverseExpansionDirection "
29686
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::ShapeDetectionLevelSetImageFilter "
29688
Default Constructor that takes no arguments and initializes default
29693
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::ToString "
29695
Print ourselves out
29699
%feature("docstring") itk::simple::ShapeDetectionLevelSetImageFilter::~ShapeDetectionLevelSetImageFilter "
29706
%feature("docstring") itk::simple::ShiftScaleImageFilter "
29708
Shift and scale the pixels in an image.
29711
ShiftScaleImageFilter shifts the input pixel by Shift (default 0.0) and then scales the
29712
pixel by Scale (default 1.0). All computattions are performed in the
29713
precision of the input pixel's RealType. Before assigning the computed
29714
value to the output pixel, the value is clamped at the NonpositiveMin
29715
and max of the pixel type.
29717
itk::simple::ShiftScale for the procedural interface
29719
itk::ShiftScaleImageFilter for the Doxygen on the original ITK class.
29722
C++ includes: sitkShiftScaleImageFilter.h
29725
%feature("docstring") itk::simple::ShiftScaleImageFilter::Execute "
29727
Execute the filter on the input image
29731
%feature("docstring") itk::simple::ShiftScaleImageFilter::Execute "
29733
Execute the filter on the input image with the given parameters
29737
%feature("docstring") itk::simple::ShiftScaleImageFilter::GetName "
29743
%feature("docstring") itk::simple::ShiftScaleImageFilter::GetScale "
29745
Set/Get the amount to Scale each Pixel. The Scale is applied after the
29750
%feature("docstring") itk::simple::ShiftScaleImageFilter::GetShift "
29752
Set/Get the amount to Shift each Pixel. The shift is followed by a
29757
%feature("docstring") itk::simple::ShiftScaleImageFilter::SetScale "
29759
Set/Get the amount to Scale each Pixel. The Scale is applied after the
29764
%feature("docstring") itk::simple::ShiftScaleImageFilter::SetShift "
29766
Set/Get the amount to Shift each Pixel. The shift is followed by a
29771
%feature("docstring") itk::simple::ShiftScaleImageFilter::ShiftScaleImageFilter "
29773
Default Constructor that takes no arguments and initializes default
29778
%feature("docstring") itk::simple::ShiftScaleImageFilter::ToString "
29780
Print ourselves out
29784
%feature("docstring") itk::simple::ShiftScaleImageFilter::~ShiftScaleImageFilter "
29791
%feature("docstring") itk::simple::ShotNoiseImageFilter "
29793
Alter an image with shot noise.
29796
The shot noise follows a Poisson distribution:
29801
where $ N(I_0) $ is a Poisson-distributed random variable of mean $ I_0 $ . The noise is thus dependent on the pixel intensities in the image.
29802
The intensities in the image can be scaled by a user provided value
29803
to map pixel values to the actual number of particles. The scaling can
29804
be seen as the inverse of the gain used during the acquisition. The
29805
noisy signal is then scaled back to its input intensity range:
29808
$ I = \\\\frac{N(I_0 \\\\times s)}{s} $
29810
where $ s $ is the scale factor.
29811
The Poisson-distributed variable $ \\\\lambda $ is computed by using the algorithm:
29814
$ \\\\begin{array}{l} k \\\\leftarrow 0 \\\\\\\\ p \\\\leftarrow 1
29815
\\\\\\\\ \\\\textbf{repeat} \\\\\\\\ \\\\left\\\\{ \\\\begin{array}{l}
29816
k \\\\leftarrow k+1 \\\\\\\\ p \\\\leftarrow p \\\\ast U()
29817
\\\\end{array} \\\\right. \\\\\\\\ \\\\textbf{until } p >
29818
e^{\\\\lambda} \\\\\\\\ \\\\textbf{return} (k) \\\\end{array} $
29820
where $ U() $ provides a uniformly distributed random variable in the interval $ [0,1] $ .
29821
This algorithm is very inefficient for large values of $ \\\\lambda $ , though. Fortunately, the Poisson distribution can be accurately
29822
approximated by a Gaussian distribution of mean and variance $ \\\\lambda $ when $ \\\\lambda $ is large enough. In this implementation, this value is considered to
29823
be 50. This leads to the faster algorithm:
29826
$ \\\\lambda + \\\\sqrt{\\\\lambda} \\\\times N()$
29828
where $ N() $ is a normally distributed random variable of mean 0 and variance 1.
29831
This code was contributed in the Insight Journal paper \"Noise
29832
Simulation\". https://hdl.handle.net/10380/3158
29834
itk::simple::ShotNoise for the procedural interface
29836
itk::ShotNoiseImageFilter for the Doxygen on the original ITK class.
29839
C++ includes: sitkShotNoiseImageFilter.h
29842
%feature("docstring") itk::simple::ShotNoiseImageFilter::Execute "
29844
Execute the filter on the input image
29848
%feature("docstring") itk::simple::ShotNoiseImageFilter::Execute "
29850
Execute the filter on the input image with the given parameters
29854
%feature("docstring") itk::simple::ShotNoiseImageFilter::GetName "
29860
%feature("docstring") itk::simple::ShotNoiseImageFilter::GetScale "
29862
Set/Get the value to map the pixel value to the actual particle
29863
counting. The scaling can be seen as the inverse of the gain used
29864
during the acquisition. The noisy signal is then scaled back to its
29865
input intensity range. Defaults to 1.0.
29869
%feature("docstring") itk::simple::ShotNoiseImageFilter::GetSeed "
29872
%feature("docstring") itk::simple::ShotNoiseImageFilter::SetScale "
29874
Set/Get the value to map the pixel value to the actual particle
29875
counting. The scaling can be seen as the inverse of the gain used
29876
during the acquisition. The noisy signal is then scaled back to its
29877
input intensity range. Defaults to 1.0.
29881
%feature("docstring") itk::simple::ShotNoiseImageFilter::SetSeed "
29884
%feature("docstring") itk::simple::ShotNoiseImageFilter::ShotNoiseImageFilter "
29886
Default Constructor that takes no arguments and initializes default
29891
%feature("docstring") itk::simple::ShotNoiseImageFilter::ToString "
29893
Print ourselves out
29897
%feature("docstring") itk::simple::ShotNoiseImageFilter::~ShotNoiseImageFilter "
29904
%feature("docstring") itk::simple::ShrinkImageFilter "
29906
Reduce the size of an image by an integer factor in each dimension.
29909
ShrinkImageFilter reduces the size of an image by an integer factor in each dimension.
29910
The algorithm implemented is a simple subsample. The output image size
29911
in each dimension is given by:
29913
outputSize[j] = max( std::floor(inputSize[j]/shrinkFactor[j]), 1 );
29915
NOTE: The physical centers of the input and output will be the same.
29916
Because of this, the Origin of the output may not be the same as the
29917
Origin of the input. Since this filter produces an image which is a
29918
different resolution, origin and with different pixel spacing than its
29919
input image, it needs to override several of the methods defined in ProcessObject in order to properly manage the pipeline execution model. In
29920
particular, this filter overrides
29921
ProcessObject::GenerateInputRequestedRegion() and
29922
ProcessObject::GenerateOutputInformation() .
29924
This filter is implemented as a multithreaded filter. It provides a
29925
ThreadedGenerateData() method for its implementation.
29933
itk::simple::Shrink for the procedural interface
29935
itk::ShrinkImageFilter for the Doxygen on the original ITK class.
29939
C++ includes: sitkShrinkImageFilter.h
29942
%feature("docstring") itk::simple::ShrinkImageFilter::Execute "
29944
Execute the filter on the input image
29948
%feature("docstring") itk::simple::ShrinkImageFilter::Execute "
29950
Execute the filter on the input image with the given parameters
29954
%feature("docstring") itk::simple::ShrinkImageFilter::GetName "
29960
%feature("docstring") itk::simple::ShrinkImageFilter::GetShrinkFactors "
29962
Get the shrink factors.
29966
%feature("docstring") itk::simple::ShrinkImageFilter::SetShrinkFactor "
29968
Custom public declarations
29972
%feature("docstring") itk::simple::ShrinkImageFilter::SetShrinkFactors "
29974
Set the shrink factors. Values are clamped to a minimum value of 1.
29975
Default is 1 for all dimensions.
29979
%feature("docstring") itk::simple::ShrinkImageFilter::ShrinkImageFilter "
29981
Default Constructor that takes no arguments and initializes default
29986
%feature("docstring") itk::simple::ShrinkImageFilter::ToString "
29988
Print ourselves out
29992
%feature("docstring") itk::simple::ShrinkImageFilter::~ShrinkImageFilter "
29999
%feature("docstring") itk::simple::SigmoidImageFilter "
30001
Computes the sigmoid function pixel-wise.
30004
A linear transformation is applied first on the argument of the
30005
sigmoid function. The resulting total transform is given by
30007
\\\\[ f(x) = (Max-Min) \\\\cdot \\\\frac{1}{\\\\left(1+e^{- \\\\frac{
30008
x - \\\\beta }{\\\\alpha}}\\\\right)} + Min \\\\]
30010
Every output pixel is equal to f(x). Where x is the intensity of the
30011
homologous input pixel, and alpha and beta are user-provided
30018
Pass image pixels through a sigmoid function
30020
itk::simple::Sigmoid for the procedural interface
30022
itk::SigmoidImageFilter for the Doxygen on the original ITK class.
30026
C++ includes: sitkSigmoidImageFilter.h
30029
%feature("docstring") itk::simple::SigmoidImageFilter::Execute "
30031
Execute the filter on the input image
30035
%feature("docstring") itk::simple::SigmoidImageFilter::Execute "
30037
Execute the filter on the input image with the given parameters
30041
%feature("docstring") itk::simple::SigmoidImageFilter::GetAlpha "
30044
%feature("docstring") itk::simple::SigmoidImageFilter::GetBeta "
30047
%feature("docstring") itk::simple::SigmoidImageFilter::GetName "
30053
%feature("docstring") itk::simple::SigmoidImageFilter::GetOutputMaximum "
30056
%feature("docstring") itk::simple::SigmoidImageFilter::GetOutputMinimum "
30059
%feature("docstring") itk::simple::SigmoidImageFilter::SetAlpha "
30062
%feature("docstring") itk::simple::SigmoidImageFilter::SetBeta "
30065
%feature("docstring") itk::simple::SigmoidImageFilter::SetOutputMaximum "
30068
%feature("docstring") itk::simple::SigmoidImageFilter::SetOutputMinimum "
30071
%feature("docstring") itk::simple::SigmoidImageFilter::SigmoidImageFilter "
30073
Default Constructor that takes no arguments and initializes default
30078
%feature("docstring") itk::simple::SigmoidImageFilter::ToString "
30080
Print ourselves out
30084
%feature("docstring") itk::simple::SigmoidImageFilter::~SigmoidImageFilter "
30091
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter "
30093
This class is parametrized over the type of the input image and the
30094
type of the output image.
30096
This filter computes the distance map of the input image as an
30097
approximation with pixel accuracy to the Euclidean distance.
30099
For purposes of evaluating the signed distance map, the input is
30100
assumed to be binary composed of pixels with value 0 and non-zero.
30102
The inside is considered as having negative distances. Outside is
30103
treated as having positive distances. To change the convention, use
30104
the InsideIsPositive(bool) function.
30106
As a convention, the distance is evaluated from the boundary of the ON
30112
A signed distance map with the approximation to the euclidean
30115
A voronoi partition. (See itkDanielssonDistanceMapImageFilter)
30117
A vector map containing the component of the vector relating the
30118
current pixel with the closest point of the closest object to this
30119
pixel. Given that the components of the distance are computed in
30120
\"pixels\", the vector is represented by an itk::Offset . That is, physical coordinates are not used. (See
30121
itkDanielssonDistanceMapImageFilter)
30122
This filter internally uses the DanielssonDistanceMap filter. This
30123
filter is N-dimensional.
30127
itkDanielssonDistanceMapImageFilter
30129
itk::simple::SignedDanielssonDistanceMap for the procedural interface
30131
itk::SignedDanielssonDistanceMapImageFilter for the Doxygen on the original ITK class.
30134
C++ includes: sitkSignedDanielssonDistanceMapImageFilter.h
30137
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::Execute "
30139
Execute the filter on the input image
30143
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::Execute "
30145
Execute the filter on the input image with the given parameters
30149
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::GetInsideIsPositive "
30151
Get if the inside represents positive values in the signed distance
30152
map. See GetInsideIsPositive()
30156
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::GetName "
30162
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::GetSquaredDistance "
30164
Get the distance squared.
30168
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::GetUseImageSpacing "
30170
Get whether spacing is used.
30174
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::InsideIsPositiveOff "
30177
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::InsideIsPositiveOn "
30179
Set the value of InsideIsPositive to true or false respectfully.
30183
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SetInsideIsPositive "
30185
Set if the inside represents positive values in the signed distance
30186
map. By convention ON pixels are treated as inside pixels.
30190
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SetSquaredDistance "
30192
Set if the distance should be squared.
30196
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SetUseImageSpacing "
30198
Set if image spacing should be used in computing distances.
30202
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SignedDanielssonDistanceMapImageFilter "
30204
Default Constructor that takes no arguments and initializes default
30209
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SquaredDistanceOff "
30212
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::SquaredDistanceOn "
30214
Set the value of SquaredDistance to true or false respectfully.
30218
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::ToString "
30220
Print ourselves out
30224
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::UseImageSpacingOff "
30227
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::UseImageSpacingOn "
30229
Set the value of UseImageSpacing to true or false respectfully.
30233
%feature("docstring") itk::simple::SignedDanielssonDistanceMapImageFilter::~SignedDanielssonDistanceMapImageFilter "
30240
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter "
30242
This filter calculates the Euclidean distance transform of a binary
30243
image in linear time for arbitrary dimensions.
30247
This is an image-to-image filter. The dimensionality is arbitrary. The
30248
only dimensionality constraint is that the input and output images be
30249
of the same dimensions and size. To maintain integer arithmetic within
30250
the filter, the default output is the signed squared distance. This
30251
implies that the input image should be of type \"unsigned int\" or
30252
\"int\" whereas the output image is of type \"int\". Obviously, if the
30253
user wishes to utilize the image spacing or to have a filter with the
30254
Euclidean distance (as opposed to the squared distance), output image
30255
types of float or double should be used.
30256
The inside is considered as having negative distances. Outside is
30257
treated as having positive distances. To change the convention, use
30258
the InsideIsPositive(bool) function.
30261
Set/GetBackgroundValue specifies the background of the value of the
30262
input binary image. Normally this is zero and, as such, zero is the
30263
default value. Other than that, the usage is completely analogous to
30264
the itk::DanielssonDistanceImageFilter class except it does not return
30266
Reference: C. R. Maurer, Jr., R. Qi, and V. Raghavan, \"A Linear Time
30267
Algorithm for Computing Exact Euclidean Distance Transforms of Binary
30268
Images in Arbitrary Dimensions\", IEEE - Transactions on Pattern
30269
Analysis and Machine Intelligence, 25(2): 265-270, 2003.
30271
itk::simple::SignedMaurerDistanceMap for the procedural interface
30273
itk::SignedMaurerDistanceMapImageFilter for the Doxygen on the original ITK class.
30276
C++ includes: sitkSignedMaurerDistanceMapImageFilter.h
30279
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::Execute "
30281
Execute the filter on the input image
30285
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::Execute "
30287
Execute the filter on the input image with the given parameters
30291
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::GetInsideIsPositive "
30293
Get if the inside represents positive values in the signed distance
30296
GetInsideIsPositive()
30301
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::GetName "
30307
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::GetSquaredDistance "
30309
Get the distance squared.
30313
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::GetUseImageSpacing "
30315
Get whether spacing is used.
30319
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::InsideIsPositiveOff "
30322
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::InsideIsPositiveOn "
30324
Set the value of InsideIsPositive to true or false respectfully.
30328
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SetInsideIsPositive "
30330
Set if the inside represents positive values in the signed distance
30331
map. By convention ON pixels are treated as inside pixels.
30335
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SetSquaredDistance "
30337
Set if the distance should be squared.
30341
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SetUseImageSpacing "
30343
Set if image spacing should be used in computing distances.
30347
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SignedMaurerDistanceMapImageFilter "
30349
Default Constructor that takes no arguments and initializes default
30354
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SquaredDistanceOff "
30357
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::SquaredDistanceOn "
30359
Set the value of SquaredDistance to true or false respectfully.
30363
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::ToString "
30365
Print ourselves out
30369
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::UseImageSpacingOff "
30372
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::UseImageSpacingOn "
30374
Set the value of UseImageSpacing to true or false respectfully.
30378
%feature("docstring") itk::simple::SignedMaurerDistanceMapImageFilter::~SignedMaurerDistanceMapImageFilter "
30385
%feature("docstring") itk::simple::Similarity2DTransform "
30387
A similarity 2D transform with rotation in radians and isotropic
30388
scaling around a fixed center with translation.
30393
itk::Similarity2DTransform
30396
C++ includes: sitkSimilarity2DTransform.h
30399
%feature("docstring") itk::simple::Similarity2DTransform::GetAngle "
30402
%feature("docstring") itk::simple::Similarity2DTransform::GetCenter "
30405
%feature("docstring") itk::simple::Similarity2DTransform::GetMatrix "
30411
%feature("docstring") itk::simple::Similarity2DTransform::GetName "
30417
%feature("docstring") itk::simple::Similarity2DTransform::GetScale "
30420
%feature("docstring") itk::simple::Similarity2DTransform::GetTranslation "
30423
%feature("docstring") itk::simple::Similarity2DTransform::SetAngle "
30429
%feature("docstring") itk::simple::Similarity2DTransform::SetCenter "
30435
%feature("docstring") itk::simple::Similarity2DTransform::SetMatrix "
30438
%feature("docstring") itk::simple::Similarity2DTransform::SetScale "
30441
%feature("docstring") itk::simple::Similarity2DTransform::SetTranslation "
30444
%feature("docstring") itk::simple::Similarity2DTransform::Similarity2DTransform "
30447
%feature("docstring") itk::simple::Similarity2DTransform::Similarity2DTransform "
30450
%feature("docstring") itk::simple::Similarity2DTransform::Similarity2DTransform "
30453
%feature("docstring") itk::simple::Similarity2DTransform::Similarity2DTransform "
30457
%feature("docstring") itk::simple::Similarity3DTransform "
30459
A similarity 3D transform with rotation as a versor, and isotropic
30460
scaling around a fixed center with translation.
30465
itk::Similarity3DTransform
30468
C++ includes: sitkSimilarity3DTransform.h
30471
%feature("docstring") itk::simple::Similarity3DTransform::GetCenter "
30474
%feature("docstring") itk::simple::Similarity3DTransform::GetMatrix "
30477
%feature("docstring") itk::simple::Similarity3DTransform::GetName "
30483
%feature("docstring") itk::simple::Similarity3DTransform::GetScale "
30486
%feature("docstring") itk::simple::Similarity3DTransform::GetTranslation "
30489
%feature("docstring") itk::simple::Similarity3DTransform::GetVersor "
30492
%feature("docstring") itk::simple::Similarity3DTransform::SetCenter "
30498
%feature("docstring") itk::simple::Similarity3DTransform::SetMatrix "
30501
%feature("docstring") itk::simple::Similarity3DTransform::SetRotation "
30507
%feature("docstring") itk::simple::Similarity3DTransform::SetRotation "
30510
%feature("docstring") itk::simple::Similarity3DTransform::SetScale "
30513
%feature("docstring") itk::simple::Similarity3DTransform::SetTranslation "
30516
%feature("docstring") itk::simple::Similarity3DTransform::Similarity3DTransform "
30519
%feature("docstring") itk::simple::Similarity3DTransform::Similarity3DTransform "
30522
%feature("docstring") itk::simple::Similarity3DTransform::Similarity3DTransform "
30525
%feature("docstring") itk::simple::Similarity3DTransform::Similarity3DTransform "
30528
%feature("docstring") itk::simple::Similarity3DTransform::Similarity3DTransform "
30531
%feature("docstring") itk::simple::Similarity3DTransform::Translate "
30538
%feature("docstring") itk::simple::SimilarityIndexImageFilter "
30540
Measures the similarity between the set of non-zero pixels of two
30544
SimilarityIndexImageFilter measures the similarity between the set non-zero pixels of two images
30545
using the following formula: \\\\[ S = \\\\frac{2 | A \\\\cap B |}{|A| + |B|} \\\\] where $A$ and $B$ are respectively the set of non-zero pixels in the first and second
30546
input images. Operator $|\\\\cdot|$ represents the size of a set and $\\\\cap$ represents the intersection of two sets.
30548
The measure is derived from a reliability measure known as the kappa
30549
statistic. $S$ is sensitive to both differences in size and in location and have
30550
been in the literature for comparing two segmentation masks. For more
30551
information see: \"Morphometric Analysis of White Matter Lesions in MR
30552
Images: Method and Validation\", A. P. Zijdenbos, B. M. Dawant, R. A.
30553
Margolin and A. C. Palmer, IEEE Trans. on Medical Imaging, 13(4) pp
30556
This filter requires the largest possible region of the first image
30557
and the same corresponding region in the second image. It behaves as
30558
filter with two input and one output. Thus it can be inserted in a
30559
pipeline with other filters. The filter passes the first input through
30562
This filter is templated over the two input image type. It assume both
30563
image have the same number of dimensions.
30567
itk::SimilarityIndexImageFilter for the Doxygen on the original ITK class.
30570
C++ includes: sitkSimilarityIndexImageFilter.h
30573
%feature("docstring") itk::simple::SimilarityIndexImageFilter::Execute "
30575
Execute the filter on the input images
30579
%feature("docstring") itk::simple::SimilarityIndexImageFilter::GetName "
30585
%feature("docstring") itk::simple::SimilarityIndexImageFilter::GetSimilarityIndex "
30587
Return the computed similarity index.
30589
This is a measurement. Its value is updated in the Execute methods, so
30590
the value will only be valid after an execution.
30594
%feature("docstring") itk::simple::SimilarityIndexImageFilter::SimilarityIndexImageFilter "
30596
Default Constructor that takes no arguments and initializes default
30601
%feature("docstring") itk::simple::SimilarityIndexImageFilter::ToString "
30603
Print ourselves out
30607
%feature("docstring") itk::simple::SimilarityIndexImageFilter::~SimilarityIndexImageFilter "
30614
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter "
30616
Computes an image of contours which will be the contour of the first
30620
A pixel of the source image is considered to belong to the contour if
30621
its pixel value is equal to the input foreground value and it has in
30622
its neighborhood at least one pixel which its pixel value is equal to
30623
the input background value. The output image will have pixels which
30624
will be set to the output foreground value if they belong to the
30625
contour, otherwise they will be set to the output background value.
30627
The neighborhood \"radius\" is set thanks to the radius params.
30635
NeighborhoodOperator
30637
NeighborhoodIterator
30639
itk::simple::SimpleContourExtractor for the procedural interface
30641
itk::SimpleContourExtractorImageFilter for the Doxygen on the original ITK class.
30644
C++ includes: sitkSimpleContourExtractorImageFilter.h
30647
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::Execute "
30649
Execute the filter on the input image
30653
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::Execute "
30655
Execute the filter on the input image with the given parameters
30659
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetInputBackgroundValue "
30661
Get the background value used in order to identify a background pixel
30662
in the input image.
30666
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetInputForegroundValue "
30668
Get the foreground value used in order to identify a foreground pixel
30669
in the input image.
30673
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetName "
30679
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetOutputBackgroundValue "
30681
Get the background value used in order to identify a background pixel
30682
in the output image.
30686
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetOutputForegroundValue "
30688
Get the foreground value used in order to identify a foreground pixel
30689
in the output image.
30693
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::GetRadius "
30696
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetInputBackgroundValue "
30698
Set the background value used in order to identify a background pixel
30699
in the input image.
30703
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetInputForegroundValue "
30705
Set the foreground value used in order to identify a foreground pixel
30706
in the input image.
30710
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetOutputBackgroundValue "
30712
Set the background value used in order to identify a background pixel
30713
in the output image.
30717
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetOutputForegroundValue "
30719
Set the foreground value used in order to identify a foreground pixel
30720
in the output image.
30724
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetRadius "
30727
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SetRadius "
30729
Set the values of the Radius vector all to value
30733
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::SimpleContourExtractorImageFilter "
30735
Default Constructor that takes no arguments and initializes default
30740
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::ToString "
30742
Print ourselves out
30746
%feature("docstring") itk::simple::SimpleContourExtractorImageFilter::~SimpleContourExtractorImageFilter "
30753
%feature("docstring") itk::simple::SinImageFilter "
30755
Computes the sine of each pixel.
30758
The computations are performed using std::sin(x).
30764
Compute the sine of each pixel.
30766
itk::simple::Sin for the procedural interface
30768
itk::SinImageFilter for the Doxygen on the original ITK class.
30772
C++ includes: sitkSinImageFilter.h
30775
%feature("docstring") itk::simple::SinImageFilter::Execute "
30777
Execute the filter on the input image
30781
%feature("docstring") itk::simple::SinImageFilter::GetName "
30787
%feature("docstring") itk::simple::SinImageFilter::SinImageFilter "
30789
Default Constructor that takes no arguments and initializes default
30794
%feature("docstring") itk::simple::SinImageFilter::ToString "
30796
Print ourselves out
30800
%feature("docstring") itk::simple::SinImageFilter::~SinImageFilter "
30807
%feature("docstring") itk::simple::SliceImageFilter "
30811
itk::simple::Slice for the procedural interface
30813
itk::SliceImageFilter for the Doxygen on the original ITK class.
30816
C++ includes: sitkSliceImageFilter.h
30819
%feature("docstring") itk::simple::SliceImageFilter::Execute "
30821
Execute the filter on the input image
30825
%feature("docstring") itk::simple::SliceImageFilter::Execute "
30827
Execute the filter on the input image with the given parameters
30831
%feature("docstring") itk::simple::SliceImageFilter::GetName "
30837
%feature("docstring") itk::simple::SliceImageFilter::GetStart "
30840
%feature("docstring") itk::simple::SliceImageFilter::GetStep "
30843
%feature("docstring") itk::simple::SliceImageFilter::GetStop "
30846
%feature("docstring") itk::simple::SliceImageFilter::SetStart "
30849
%feature("docstring") itk::simple::SliceImageFilter::SetStep "
30852
%feature("docstring") itk::simple::SliceImageFilter::SetStep "
30854
Set the values of the Step vector all to value
30858
%feature("docstring") itk::simple::SliceImageFilter::SetStop "
30861
%feature("docstring") itk::simple::SliceImageFilter::SliceImageFilter "
30863
Default Constructor that takes no arguments and initializes default
30868
%feature("docstring") itk::simple::SliceImageFilter::ToString "
30870
Print ourselves out
30874
%feature("docstring") itk::simple::SliceImageFilter::~SliceImageFilter "
30881
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter "
30883
Computes the smoothing of an image by convolution with the Gaussian
30884
kernels implemented as IIR filters.
30887
This filter is implemented using the recursive gaussian filters. For
30888
multi-component images, the filter works on each component
30891
For this filter to be able to run in-place the input and output image
30892
types need to be the same and/or the same type as the RealImageType.
30898
Gaussian smoothing that works with image adaptors
30900
itk::simple::SmoothingRecursiveGaussian for the procedural interface
30902
itk::SmoothingRecursiveGaussianImageFilter for the Doxygen on the original ITK class.
30906
C++ includes: sitkSmoothingRecursiveGaussianImageFilter.h
30909
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::Execute "
30911
Execute the filter on the input image
30915
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::Execute "
30917
Execute the filter on the input image with the given parameters
30921
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::GetName "
30927
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::GetNormalizeAcrossScale "
30929
This method does not effect the output of this filter.
30931
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
30936
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::GetSigma "
30939
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::NormalizeAcrossScaleOff "
30942
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::NormalizeAcrossScaleOn "
30944
Set the value of NormalizeAcrossScale to true or false respectfully.
30948
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::SetNormalizeAcrossScale "
30950
This method does not effect the output of this filter.
30952
RecursiveGaussianImageFilter::SetNormalizeAcrossScale
30957
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::SetSigma "
30959
Set Sigma value. Sigma is measured in the units of image spacing. You
30960
may use the method SetSigma to set the same value across each axis or
30961
use the method SetSigmaArray if you need different values along each
30966
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::SmoothingRecursiveGaussianImageFilter "
30968
Default Constructor that takes no arguments and initializes default
30973
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::ToString "
30975
Print ourselves out
30979
%feature("docstring") itk::simple::SmoothingRecursiveGaussianImageFilter::~SmoothingRecursiveGaussianImageFilter "
30986
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter "
30988
A 2D or 3D edge detection using the Sobel operator.
30991
This filter uses the Sobel operator to calculate the image gradient
30992
and then finds the magnitude of this gradient vector. The Sobel
30993
gradient magnitude (square-root sum of squares) is an indication of
31004
NeighborhoodOperator
31006
NeighborhoodIterator
31011
SobelEdgeDetectionImageFilter
31013
itk::simple::SobelEdgeDetection for the procedural interface
31015
itk::SobelEdgeDetectionImageFilter for the Doxygen on the original ITK class.
31019
C++ includes: sitkSobelEdgeDetectionImageFilter.h
31022
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter::Execute "
31024
Execute the filter on the input image
31028
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter::GetName "
31034
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter::SobelEdgeDetectionImageFilter "
31036
Default Constructor that takes no arguments and initializes default
31041
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter::ToString "
31043
Print ourselves out
31047
%feature("docstring") itk::simple::SobelEdgeDetectionImageFilter::~SobelEdgeDetectionImageFilter "
31054
%feature("docstring") itk::simple::SpeckleNoiseImageFilter "
31056
Alter an image with speckle (multiplicative) noise.
31059
The speckle noise follows a Gamma distribution of mean 1 and standard
31060
deviation provided by the user. The noise is proportional to the pixel
31065
This code was contributed in the Insight Journal paper \"Noise
31066
Simulation\". https://hdl.handle.net/10380/3158
31068
itk::simple::SpeckleNoise for the procedural interface
31070
itk::SpeckleNoiseImageFilter for the Doxygen on the original ITK class.
31073
C++ includes: sitkSpeckleNoiseImageFilter.h
31076
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::Execute "
31078
Execute the filter on the input image
31082
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::Execute "
31084
Execute the filter on the input image with the given parameters
31088
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::GetName "
31094
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::GetSeed "
31097
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::GetStandardDeviation "
31100
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::SetSeed "
31103
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::SetStandardDeviation "
31106
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::SpeckleNoiseImageFilter "
31108
Default Constructor that takes no arguments and initializes default
31113
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::ToString "
31115
Print ourselves out
31119
%feature("docstring") itk::simple::SpeckleNoiseImageFilter::~SpeckleNoiseImageFilter "
31126
%feature("docstring") itk::simple::SqrtImageFilter "
31128
Computes the square root of each pixel.
31131
The computations are performed using std::sqrt(x).
31133
itk::simple::Sqrt for the procedural interface
31135
itk::SqrtImageFilter for the Doxygen on the original ITK class.
31138
C++ includes: sitkSqrtImageFilter.h
31141
%feature("docstring") itk::simple::SqrtImageFilter::Execute "
31143
Execute the filter on the input image
31147
%feature("docstring") itk::simple::SqrtImageFilter::GetName "
31153
%feature("docstring") itk::simple::SqrtImageFilter::SqrtImageFilter "
31155
Default Constructor that takes no arguments and initializes default
31160
%feature("docstring") itk::simple::SqrtImageFilter::ToString "
31162
Print ourselves out
31166
%feature("docstring") itk::simple::SqrtImageFilter::~SqrtImageFilter "
31173
%feature("docstring") itk::simple::SquareImageFilter "
31175
Computes the square of the intensity values pixel-wise.
31182
Square every pixel in an image
31184
itk::simple::Square for the procedural interface
31186
itk::SquareImageFilter for the Doxygen on the original ITK class.
31190
C++ includes: sitkSquareImageFilter.h
31193
%feature("docstring") itk::simple::SquareImageFilter::Execute "
31195
Execute the filter on the input image
31199
%feature("docstring") itk::simple::SquareImageFilter::GetName "
31205
%feature("docstring") itk::simple::SquareImageFilter::SquareImageFilter "
31207
Default Constructor that takes no arguments and initializes default
31212
%feature("docstring") itk::simple::SquareImageFilter::ToString "
31214
Print ourselves out
31218
%feature("docstring") itk::simple::SquareImageFilter::~SquareImageFilter "
31225
%feature("docstring") itk::simple::SquaredDifferenceImageFilter "
31227
Implements pixel-wise the computation of squared difference.
31230
This filter is parametrized over the types of the two input images and
31231
the type of the output image.
31233
Numeric conversions (castings) are done by the C++ defaults.
31235
The filter will walk over all the pixels in the two input images, and
31236
for each one of them it will do the following:
31239
cast the input 1 pixel value to double
31241
cast the input 2 pixel value to double
31243
compute the difference of the two pixel values
31245
compute the square of the difference
31247
cast the double value resulting from sqr() to the pixel type of the output image
31249
store the casted value into the output image.
31250
The filter expect all images to have the same dimension (e.g. all 2D,
31251
or all 3D, or all ND)
31257
Compute the squared difference of corresponding pixels in two images
31259
itk::simple::SquaredDifference for the procedural interface
31261
itk::SquaredDifferenceImageFilter for the Doxygen on the original ITK class.
31265
C++ includes: sitkSquaredDifferenceImageFilter.h
31268
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::Execute "
31270
Execute the filter on the input images
31274
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::Execute "
31276
Execute the filter with an image and a constant
31280
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::Execute "
31283
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::GetName "
31289
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::SquaredDifferenceImageFilter "
31291
Default Constructor that takes no arguments and initializes default
31296
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::ToString "
31298
Print ourselves out
31302
%feature("docstring") itk::simple::SquaredDifferenceImageFilter::~SquaredDifferenceImageFilter "
31309
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter "
31314
This class was contributed to the Insight Journal by Gaetan Lehmann.
31315
The original paper can be found at https://hdl.handle.net/1926/164
31318
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
31319
de Jouy-en-Josas, France.
31322
ProjectionImageFilter
31324
MedianProjectionImageFilter
31326
MeanProjectionImageFilter
31328
SumProjectionImageFilter
31330
MeanProjectionImageFilter
31332
MaximumProjectionImageFilter
31334
MinimumProjectionImageFilter
31336
BinaryProjectionImageFilter
31338
itk::simple::StandardDeviationProjection for the procedural interface
31340
itk::StandardDeviationProjectionImageFilter for the Doxygen on the original ITK class.
31343
C++ includes: sitkStandardDeviationProjectionImageFilter.h
31346
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::Execute "
31348
Execute the filter on the input image
31352
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::Execute "
31354
Execute the filter on the input image with the given parameters
31358
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::GetName "
31364
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::GetProjectionDimension "
31367
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::SetProjectionDimension "
31370
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::StandardDeviationProjectionImageFilter "
31372
Default Constructor that takes no arguments and initializes default
31377
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::ToString "
31379
Print ourselves out
31383
%feature("docstring") itk::simple::StandardDeviationProjectionImageFilter::~StandardDeviationProjectionImageFilter "
31390
%feature("docstring") itk::simple::StatisticsImageFilter "
31392
Compute min. max, variance and mean of an Image .
31395
StatisticsImageFilter computes the minimum, maximum, sum, mean, variance sigma of an image.
31396
The filter needs all of its input image. It behaves as a filter with
31397
an input and output. Thus it can be inserted in a pipline with other
31398
filters and the statistics will only be recomputed if a downstream
31401
The filter passes its input through unmodified. The filter is
31402
threaded. It computes statistics in each thread then combines them in
31403
its AfterThreadedGenerate method.
31409
Compute min, max, variance and mean of an Image.
31412
itk::StatisticsImageFilter for the Doxygen on the original ITK class.
31415
C++ includes: sitkStatisticsImageFilter.h
31418
%feature("docstring") itk::simple::StatisticsImageFilter::Execute "
31420
Execute the filter on the input image
31424
%feature("docstring") itk::simple::StatisticsImageFilter::GetMaximum "
31426
Return the computed Maximum.
31428
This is a measurement. Its value is updated in the Execute methods, so
31429
the value will only be valid after an execution.
31433
%feature("docstring") itk::simple::StatisticsImageFilter::GetMean "
31435
Return the computed Mean.
31437
This is a measurement. Its value is updated in the Execute methods, so
31438
the value will only be valid after an execution.
31442
%feature("docstring") itk::simple::StatisticsImageFilter::GetMinimum "
31444
Return the computed Minimum.
31446
This is a measurement. Its value is updated in the Execute methods, so
31447
the value will only be valid after an execution.
31451
%feature("docstring") itk::simple::StatisticsImageFilter::GetName "
31457
%feature("docstring") itk::simple::StatisticsImageFilter::GetSigma "
31459
Return the computed Standard Deviation.
31461
This is a measurement. Its value is updated in the Execute methods, so
31462
the value will only be valid after an execution.
31466
%feature("docstring") itk::simple::StatisticsImageFilter::GetSum "
31468
Return the compute Sum.
31470
This is a measurement. Its value is updated in the Execute methods, so
31471
the value will only be valid after an execution.
31475
%feature("docstring") itk::simple::StatisticsImageFilter::GetVariance "
31477
Return the computed Variance.
31479
This is a measurement. Its value is updated in the Execute methods, so
31480
the value will only be valid after an execution.
31484
%feature("docstring") itk::simple::StatisticsImageFilter::StatisticsImageFilter "
31486
Default Constructor that takes no arguments and initializes default
31491
%feature("docstring") itk::simple::StatisticsImageFilter::ToString "
31493
Print ourselves out
31497
%feature("docstring") itk::simple::StatisticsImageFilter::~StatisticsImageFilter "
31504
%feature("docstring") itk::simple::SubtractImageFilter "
31506
Pixel-wise subtraction of two images.
31509
Subtract each pixel from image2 from its corresponding pixel in
31516
This class is templated over the types of the two input images and the
31517
type of the output image. Numeric conversions (castings) are done by
31520
Additionally, a constant can be subtracted from every pixel in an
31525
The result of AddImageFilter with a negative constant is not necessarily the same as SubtractImageFilter . This would be the case when the PixelType defines an operator-() that is not the inverse of operator+()
31530
Subtract two images
31532
Subtract a constant from every pixel in an image
31534
itk::simple::Subtract for the procedural interface
31536
itk::SubtractImageFilter for the Doxygen on the original ITK class.
31540
C++ includes: sitkSubtractImageFilter.h
31543
%feature("docstring") itk::simple::SubtractImageFilter::Execute "
31545
Execute the filter on the input images
31549
%feature("docstring") itk::simple::SubtractImageFilter::Execute "
31551
Execute the filter with an image and a constant
31555
%feature("docstring") itk::simple::SubtractImageFilter::Execute "
31558
%feature("docstring") itk::simple::SubtractImageFilter::GetName "
31564
%feature("docstring") itk::simple::SubtractImageFilter::SubtractImageFilter "
31566
Default Constructor that takes no arguments and initializes default
31571
%feature("docstring") itk::simple::SubtractImageFilter::ToString "
31573
Print ourselves out
31577
%feature("docstring") itk::simple::SubtractImageFilter::~SubtractImageFilter "
31584
%feature("docstring") itk::simple::SumProjectionImageFilter "
31589
This class was contributed to the Insight Journal by Gaetan Lehmann.
31590
The original paper can be found at https://hdl.handle.net/1926/164
31593
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
31594
de Jouy-en-Josas, France.
31597
ProjectionImageFilter
31599
MedianProjectionImageFilter
31601
MeanProjectionImageFilter
31603
MeanProjectionImageFilter
31605
MaximumProjectionImageFilter
31607
MinimumProjectionImageFilter
31609
BinaryProjectionImageFilter
31611
StandardDeviationProjectionImageFilter
31613
itk::simple::SumProjection for the procedural interface
31615
itk::SumProjectionImageFilter for the Doxygen on the original ITK class.
31618
C++ includes: sitkSumProjectionImageFilter.h
31621
%feature("docstring") itk::simple::SumProjectionImageFilter::Execute "
31623
Execute the filter on the input image
31627
%feature("docstring") itk::simple::SumProjectionImageFilter::Execute "
31629
Execute the filter on the input image with the given parameters
31633
%feature("docstring") itk::simple::SumProjectionImageFilter::GetName "
31639
%feature("docstring") itk::simple::SumProjectionImageFilter::GetProjectionDimension "
31642
%feature("docstring") itk::simple::SumProjectionImageFilter::SetProjectionDimension "
31645
%feature("docstring") itk::simple::SumProjectionImageFilter::SumProjectionImageFilter "
31647
Default Constructor that takes no arguments and initializes default
31652
%feature("docstring") itk::simple::SumProjectionImageFilter::ToString "
31654
Print ourselves out
31658
%feature("docstring") itk::simple::SumProjectionImageFilter::~SumProjectionImageFilter "
31665
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter "
31667
Deformably register two images using the demons algorithm.
31670
This class was contributed by Corinne Mattmann, ETH Zurich,
31671
Switzerland. based on a variation of the DemonsRegistrationFilter . The basic modification is to use equation (5) from Thirion's paper
31672
along with the modification for avoiding large deformations when
31673
gradients have small values.
31675
SymmetricForcesDemonsRegistrationFilter implements the demons deformable algorithm that register two images
31676
by computing the deformation field which will map a moving image onto
31679
A deformation field is represented as a image whose pixel type is some
31680
vector type with at least N elements, where N is the dimension of the
31681
fixed image. The vector type must support element access via operator
31682
[]. It is assumed that the vector elements behave like floating point
31685
This class is templated over the fixed image type, moving image type
31686
and the deformation field type.
31688
The input fixed and moving images are set via methods SetFixedImage
31689
and SetMovingImage respectively. An initial deformation field maybe
31690
set via SetInitialDisplacementField or SetInput. If no initial field
31691
is set, a zero field is used as the initial condition.
31693
The algorithm has one parameters: the number of iteration to be
31696
The output deformation field can be obtained via methods GetOutput or
31697
GetDisplacementField.
31699
This class make use of the finite difference solver hierarchy. Update
31700
for each iteration is computed in DemonsRegistrationFunction .
31704
This filter assumes that the fixed image type, moving image type and
31705
deformation field type all have the same number of dimensions.
31708
SymmetricForcesDemonsRegistrationFunction
31710
DemonsRegistrationFilter
31712
DemonsRegistrationFunction
31714
itk::SymmetricForcesDemonsRegistrationFilter for the Doxygen on the original ITK class.
31717
C++ includes: sitkSymmetricForcesDemonsRegistrationFilter.h
31720
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::Execute "
31722
Execute the filter on the input image
31726
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::Execute "
31729
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::Execute "
31731
Execute the filter on the input image with the given parameters
31735
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::Execute "
31738
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetElapsedIterations "
31740
Number of iterations run.
31743
This is an active measurement. It may be accessed while the filter is
31744
being executing in command call-backs and can be accessed after
31749
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetIntensityDifferenceThreshold "
31752
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetMaximumError "
31754
Set/Get the desired maximum error of the Guassian kernel approximate.
31758
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetMaximumKernelWidth "
31760
Set/Get the desired limits of the Gaussian kernel width.
31764
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetMaximumRMSError "
31767
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetMetric "
31769
Get the metric value. The metric value is the mean square difference
31770
in intensity between the fixed image and transforming moving image
31771
computed over the the overlapping region between the two images. This
31772
value is calculated for the current iteration
31774
This is an active measurement. It may be accessed while the filter is
31775
being executing in command call-backs and can be accessed after
31780
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetName "
31786
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetNumberOfIterations "
31789
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetRMSChange "
31791
Set/Get the root mean squared change of the previous iteration. May
31792
not be used by all solvers.
31794
This is a measurement. Its value is updated in the Execute methods, so
31795
the value will only be valid after an execution.
31799
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetSmoothDisplacementField "
31801
Set/Get whether the displacement field is smoothed (regularized).
31802
Smoothing the displacement yields a solution elastic in nature. If
31803
SmoothDisplacementField is on, then the displacement field is smoothed
31804
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
31808
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetSmoothUpdateField "
31810
Set/Get whether the update field is smoothed (regularized). Smoothing
31811
the update field yields a solution viscous in nature. If
31812
SmoothUpdateField is on, then the update field is smoothed with a
31813
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
31817
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetStandardDeviations "
31819
Set/Get the Gaussian smoothing standard deviations for the
31820
displacement field. The values are set with respect to pixel
31825
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetUpdateFieldStandardDeviations "
31827
Set the Gaussian smoothing standard deviations for the update field.
31828
The values are set with respect to pixel coordinates.
31832
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::GetUseImageSpacing "
31835
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetIntensityDifferenceThreshold "
31837
Set/Get the threshold below which the absolute difference of intensity
31838
yields a match. When the intensities match between a moving and fixed
31839
image pixel, the update vector (for that iteration) will be the zero
31840
vector. Default is 0.001.
31844
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetMaximumError "
31846
Set/Get the desired maximum error of the Guassian kernel approximate.
31850
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetMaximumKernelWidth "
31852
Set/Get the desired limits of the Gaussian kernel width.
31856
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetMaximumRMSError "
31859
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetNumberOfIterations "
31862
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetSmoothDisplacementField "
31864
Set/Get whether the displacement field is smoothed (regularized).
31865
Smoothing the displacement yields a solution elastic in nature. If
31866
SmoothDisplacementField is on, then the displacement field is smoothed
31867
with a Gaussian whose standard deviations are specified with SetStandardDeviations()
31871
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetSmoothUpdateField "
31873
Set/Get whether the update field is smoothed (regularized). Smoothing
31874
the update field yields a solution viscous in nature. If
31875
SmoothUpdateField is on, then the update field is smoothed with a
31876
Gaussian whose standard deviations are specified with SetUpdateFieldStandardDeviations()
31880
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetStandardDeviations "
31882
Set/Get the Gaussian smoothing standard deviations for the
31883
displacement field. The values are set with respect to pixel
31888
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetStandardDeviations "
31890
Set the values of the StandardDeviations vector all to value
31894
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
31896
Set the Gaussian smoothing standard deviations for the update field.
31897
The values are set with respect to pixel coordinates.
31901
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetUpdateFieldStandardDeviations "
31903
Set the values of the UpdateFieldStandardDeviations vector all to
31908
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SetUseImageSpacing "
31911
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SmoothDisplacementFieldOff "
31914
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SmoothDisplacementFieldOn "
31916
Set the value of SmoothDisplacementField to true or false
31921
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SmoothUpdateFieldOff "
31924
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SmoothUpdateFieldOn "
31926
Set the value of SmoothUpdateField to true or false respectfully.
31930
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::SymmetricForcesDemonsRegistrationFilter "
31932
Default Constructor that takes no arguments and initializes default
31937
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::ToString "
31939
Print ourselves out
31943
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::UseImageSpacingOff "
31946
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::UseImageSpacingOn "
31948
Set the value of UseImageSpacing to true or false respectfully.
31952
%feature("docstring") itk::simple::SymmetricForcesDemonsRegistrationFilter::~SymmetricForcesDemonsRegistrationFilter "
31959
%feature("docstring") itk::simple::TanImageFilter "
31961
Computes the tangent of each input pixel.
31964
The computations are performed using std::tan(x).
31966
itk::simple::Tan for the procedural interface
31968
itk::TanImageFilter for the Doxygen on the original ITK class.
31971
C++ includes: sitkTanImageFilter.h
31974
%feature("docstring") itk::simple::TanImageFilter::Execute "
31976
Execute the filter on the input image
31980
%feature("docstring") itk::simple::TanImageFilter::GetName "
31986
%feature("docstring") itk::simple::TanImageFilter::TanImageFilter "
31988
Default Constructor that takes no arguments and initializes default
31993
%feature("docstring") itk::simple::TanImageFilter::ToString "
31995
Print ourselves out
31999
%feature("docstring") itk::simple::TanImageFilter::~TanImageFilter "
32006
%feature("docstring") itk::simple::TernaryAddImageFilter "
32008
Pixel-wise addition of three images.
32011
This class is templated over the types of the three input images and
32012
the type of the output image. Numeric conversions (castings) are done
32013
by the C++ defaults.
32015
itk::simple::TernaryAdd for the procedural interface
32017
itk::TernaryAddImageFilter for the Doxygen on the original ITK class.
32020
C++ includes: sitkTernaryAddImageFilter.h
32023
%feature("docstring") itk::simple::TernaryAddImageFilter::Execute "
32025
Execute the filter on the input image
32029
%feature("docstring") itk::simple::TernaryAddImageFilter::GetName "
32035
%feature("docstring") itk::simple::TernaryAddImageFilter::TernaryAddImageFilter "
32037
Default Constructor that takes no arguments and initializes default
32042
%feature("docstring") itk::simple::TernaryAddImageFilter::ToString "
32044
Print ourselves out
32048
%feature("docstring") itk::simple::TernaryAddImageFilter::~TernaryAddImageFilter "
32055
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter "
32057
Compute the pixel-wise magnitude of three images.
32060
This class is templated over the types of the three input images and
32061
the type of the output image. Numeric conversions (castings) are done
32062
by the C++ defaults.
32064
itk::simple::TernaryMagnitude for the procedural interface
32066
itk::TernaryMagnitudeImageFilter for the Doxygen on the original ITK class.
32069
C++ includes: sitkTernaryMagnitudeImageFilter.h
32072
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter::Execute "
32074
Execute the filter on the input image
32078
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter::GetName "
32084
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter::TernaryMagnitudeImageFilter "
32086
Default Constructor that takes no arguments and initializes default
32091
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter::ToString "
32093
Print ourselves out
32097
%feature("docstring") itk::simple::TernaryMagnitudeImageFilter::~TernaryMagnitudeImageFilter "
32104
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter "
32106
Compute the pixel-wise squared magnitude of three images.
32109
This class is templated over the types of the three input images and
32110
the type of the output image. Numeric conversions (castings) are done
32111
by the C++ defaults.
32113
itk::simple::TernaryMagnitudeSquared for the procedural interface
32115
itk::TernaryMagnitudeSquaredImageFilter for the Doxygen on the original ITK class.
32118
C++ includes: sitkTernaryMagnitudeSquaredImageFilter.h
32121
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter::Execute "
32123
Execute the filter on the input image
32127
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter::GetName "
32133
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter::TernaryMagnitudeSquaredImageFilter "
32135
Default Constructor that takes no arguments and initializes default
32140
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter::ToString "
32142
Print ourselves out
32146
%feature("docstring") itk::simple::TernaryMagnitudeSquaredImageFilter::~TernaryMagnitudeSquaredImageFilter "
32153
%feature("docstring") itk::simple::ThresholdImageFilter "
32155
Set image values to a user-specified value if they are below, above,
32156
or between simple threshold values.
32159
ThresholdImageFilter sets image values to a user-specified \"outside\" value (by default,
32160
\"black\") if the image values are below, above, or between simple
32163
The available methods are:
32165
ThresholdAbove() : The values greater than the threshold value are set
32168
ThresholdBelow() : The values less than the threshold value are set to
32171
ThresholdOutside() : The values outside the threshold range (less than
32172
lower or greater than upper) are set to OutsideValue
32174
Note that these definitions indicate that pixels equal to the
32175
threshold value are not set to OutsideValue in any of these methods
32177
The pixels must support the operators >= and <=.
32185
itk::simple::Threshold for the procedural interface
32187
itk::ThresholdImageFilter for the Doxygen on the original ITK class.
32191
C++ includes: sitkThresholdImageFilter.h
32194
%feature("docstring") itk::simple::ThresholdImageFilter::Execute "
32196
Execute the filter on the input image
32200
%feature("docstring") itk::simple::ThresholdImageFilter::Execute "
32202
Execute the filter on the input image with the given parameters
32206
%feature("docstring") itk::simple::ThresholdImageFilter::GetLower "
32208
Set/Get methods to set the lower threshold.
32212
%feature("docstring") itk::simple::ThresholdImageFilter::GetName "
32218
%feature("docstring") itk::simple::ThresholdImageFilter::GetOutsideValue "
32220
Get the \"outside\" pixel value.
32224
%feature("docstring") itk::simple::ThresholdImageFilter::GetUpper "
32226
Set/Get methods to set the upper threshold.
32230
%feature("docstring") itk::simple::ThresholdImageFilter::SetLower "
32232
Set/Get methods to set the lower threshold.
32236
%feature("docstring") itk::simple::ThresholdImageFilter::SetOutsideValue "
32238
The pixel type must support comparison operators. Set the \"outside\"
32239
pixel value. The default value NumericTraits<PixelType>::ZeroValue() .
32243
%feature("docstring") itk::simple::ThresholdImageFilter::SetUpper "
32245
Set/Get methods to set the upper threshold.
32249
%feature("docstring") itk::simple::ThresholdImageFilter::ThresholdImageFilter "
32251
Default Constructor that takes no arguments and initializes default
32256
%feature("docstring") itk::simple::ThresholdImageFilter::ToString "
32258
Print ourselves out
32262
%feature("docstring") itk::simple::ThresholdImageFilter::~ThresholdImageFilter "
32269
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter "
32271
Finds the threshold value of an image based on maximizing the number
32272
of objects in the image that are larger than a given minimal size.
32276
This method is based on Topological Stable State Thresholding to
32277
calculate the threshold set point. This method is particularly
32278
effective when there are a large number of objects in a microscopy
32279
image. Compiling in Debug mode and enable the debug flag for this
32280
filter to print debug information to see how the filter focuses in on
32281
a threshold value. Please see the Insight Journal's MICCAI 2005
32282
workshop for a complete description. References are below.
32284
The MinimumObjectSizeInPixels parameter is controlled through the
32285
class Get/SetMinimumObjectSizeInPixels() method. Similar to the
32286
standard itk::BinaryThresholdImageFilter the Get/SetInside and Get/SetOutside values of the threshold can be
32287
set. The GetNumberOfObjects() and GetThresholdValue() methods return
32288
the number of objects above the minimum pixel size and the calculated
32290
Automatic Thresholding in ITK
32291
There are multiple methods to automatically calculate the threshold
32292
intensity value of an image. As of version 4.0, ITK has a Thresholding
32293
( ITKThresholding ) module which contains numerous automatic
32294
thresholding methods.implements two of these. Topological Stable State
32295
Thresholding works well on images with a large number of objects to be
32298
1) Urish KL, August J, Huard J. \"Unsupervised segmentation for
32299
myofiber counting in immunoflourescent images\". Insight Journal. ISC
32300
/NA-MIC/MICCAI Workshop on Open-Source Software (2005) Dspace handle: https://hdl.handle.net/1926/48 2) Pikaz A, Averbuch, A. \"Digital image thresholding based on
32301
topological stable-state\". Pattern Recognition, 29(5): 829-843, 1996.
32303
Questions: email Ken Urish at ken.urish(at)gmail.com Please cc the itk
32304
list serve for archival purposes.
32307
itk::simple::ThresholdMaximumConnectedComponents for the procedural interface
32309
itk::ThresholdMaximumConnectedComponentsImageFilter for the Doxygen on the original ITK class.
32312
C++ includes: sitkThresholdMaximumConnectedComponentsImageFilter.h
32315
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::Execute "
32317
Execute the filter on the input image
32321
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::Execute "
32323
Execute the filter on the input image with the given parameters
32327
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::GetInsideValue "
32329
The following Set/Get methods are for the binary threshold function.
32330
This class automatically calculates the lower threshold boundary. The
32331
upper threshold boundary, inside value, and outside value can be
32332
defined by the user, however the standard values are used as default
32333
if not set by the user. The default value of the: Inside value is the
32334
maximum pixel type intensity. Outside value is the minimum pixel type
32335
intensity. Upper threshold boundary is the maximum pixel type
32340
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::GetMinimumObjectSizeInPixels "
32342
The pixel type must support comparison operators. Set the minimum
32343
pixel area used to count objects on the image. Thus, only objects that
32344
have a pixel area greater than the minimum pixel area will be counted
32345
as an object in the optimization portion of this filter. Essentially,
32346
it eliminates noise from being counted as an object. The default value
32351
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::GetName "
32357
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::GetOutsideValue "
32359
The following Set/Get methods are for the binary threshold function.
32360
This class automatically calculates the lower threshold boundary. The
32361
upper threshold boundary, inside value, and outside value can be
32362
defined by the user, however the standard values are used as default
32363
if not set by the user. The default value of the: Inside value is the
32364
maximum pixel type intensity. Outside value is the minimum pixel type
32365
intensity. Upper threshold boundary is the maximum pixel type
32370
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::GetUpperBoundary "
32372
The following Set/Get methods are for the binary threshold function.
32373
This class automatically calculates the lower threshold boundary. The
32374
upper threshold boundary, inside value, and outside value can be
32375
defined by the user, however the standard values are used as default
32376
if not set by the user. The default value of the: Inside value is the
32377
maximum pixel type intensity. Outside value is the minimum pixel type
32378
intensity. Upper threshold boundary is the maximum pixel type
32383
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::SetInsideValue "
32385
The following Set/Get methods are for the binary threshold function.
32386
This class automatically calculates the lower threshold boundary. The
32387
upper threshold boundary, inside value, and outside value can be
32388
defined by the user, however the standard values are used as default
32389
if not set by the user. The default value of the: Inside value is the
32390
maximum pixel type intensity. Outside value is the minimum pixel type
32391
intensity. Upper threshold boundary is the maximum pixel type
32396
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::SetMinimumObjectSizeInPixels "
32398
The pixel type must support comparison operators. Set the minimum
32399
pixel area used to count objects on the image. Thus, only objects that
32400
have a pixel area greater than the minimum pixel area will be counted
32401
as an object in the optimization portion of this filter. Essentially,
32402
it eliminates noise from being counted as an object. The default value
32407
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::SetOutsideValue "
32409
The following Set/Get methods are for the binary threshold function.
32410
This class automatically calculates the lower threshold boundary. The
32411
upper threshold boundary, inside value, and outside value can be
32412
defined by the user, however the standard values are used as default
32413
if not set by the user. The default value of the: Inside value is the
32414
maximum pixel type intensity. Outside value is the minimum pixel type
32415
intensity. Upper threshold boundary is the maximum pixel type
32420
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::SetUpperBoundary "
32422
The following Set/Get methods are for the binary threshold function.
32423
This class automatically calculates the lower threshold boundary. The
32424
upper threshold boundary, inside value, and outside value can be
32425
defined by the user, however the standard values are used as default
32426
if not set by the user. The default value of the: Inside value is the
32427
maximum pixel type intensity. Outside value is the minimum pixel type
32428
intensity. Upper threshold boundary is the maximum pixel type
32433
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::ThresholdMaximumConnectedComponentsImageFilter "
32435
Default Constructor that takes no arguments and initializes default
32440
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::ToString "
32442
Print ourselves out
32446
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponentsImageFilter::~ThresholdMaximumConnectedComponentsImageFilter "
32453
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter "
32455
Segments structures in images based on intensity values.
32459
The SegmentationLevelSetImageFilter class and the ThresholdSegmentationLevelSetFunction class contain additional information necessary to the full
32460
understanding of how to use this filter.
32462
This class is a level set method segmentation filter. It constructs a
32463
speed function which is close to zero at the upper and lower bounds of
32464
an intensity window, effectively locking the propagating front onto
32465
those edges. Elsewhere, the front will propagate quickly.
32467
This filter requires two inputs. The first input is a seed image. This
32468
seed image must contain an isosurface that you want to use as the seed
32469
for your segmentation. It can be a binary, graylevel, or floating
32470
point image. The only requirement is that it contain a closed
32471
isosurface that you will identify as the seed by setting the
32472
IsosurfaceValue parameter of the filter. For a binary image you will
32473
want to set your isosurface value halfway between your on and off
32474
values (i.e. for 0's and 1's, use an isosurface value of 0.5).
32476
The second input is the feature image. This is the image from which
32477
the speed function will be calculated. For most applications, this is
32478
the image that you want to segment. The desired isosurface in your
32479
seed image should lie within the region of your feature image that you
32480
are trying to segment. Note that this filter does no preprocessing of
32481
the feature image before thresholding.
32483
See SegmentationLevelSetImageFilter for more information on Inputs.
32485
The filter outputs a single, scalar, real-valued image. Positive
32486
values in the output image are inside the segmentated region and
32487
negative values in the image are outside of the inside region. The
32488
zero crossings of the image correspond to the position of the level
32491
See SparseFieldLevelSetImageFilter and SegmentationLevelSetImageFilter for more information.
32493
In addition to parameters described in SegmentationLevelSetImageFilter , this filter adds the UpperThreshold and LowerThreshold. See ThresholdSegmentationLevelSetFunction for a description of how these values affect the segmentation.
32496
SegmentationLevelSetImageFilter
32498
ThresholdSegmentationLevelSetFunction ,
32500
SparseFieldLevelSetImageFilter
32502
itk::simple::ThresholdSegmentationLevelSet for the procedural interface
32504
itk::ThresholdSegmentationLevelSetImageFilter for the Doxygen on the original ITK class.
32507
C++ includes: sitkThresholdSegmentationLevelSetImageFilter.h
32510
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::Execute "
32512
Execute the filter on the input images
32516
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::Execute "
32518
Execute the filter on the input images with the given parameters
32522
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetCurvatureScaling "
32525
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetElapsedIterations "
32527
Number of iterations run.
32530
This is a measurement. Its value is updated in the Execute methods, so
32531
the value will only be valid after an execution.
32535
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetLowerThreshold "
32538
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetMaximumRMSError "
32541
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetName "
32547
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetNumberOfIterations "
32550
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetPropagationScaling "
32553
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetReverseExpansionDirection "
32556
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetRMSChange "
32558
The Root Mean Square of the levelset upon termination.
32561
This is a measurement. Its value is updated in the Execute methods, so
32562
the value will only be valid after an execution.
32566
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::GetUpperThreshold "
32569
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::ReverseExpansionDirectionOff "
32572
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::ReverseExpansionDirectionOn "
32574
Set the value of ReverseExpansionDirection to true or false
32579
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetCurvatureScaling "
32582
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetLowerThreshold "
32585
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetMaximumRMSError "
32588
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetNumberOfIterations "
32591
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetPropagationScaling "
32594
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetReverseExpansionDirection "
32597
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::SetUpperThreshold "
32599
Get/Set the threshold values that will be used to calculate the speed
32604
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::ThresholdSegmentationLevelSetImageFilter "
32606
Default Constructor that takes no arguments and initializes default
32611
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::ToString "
32613
Print ourselves out
32617
%feature("docstring") itk::simple::ThresholdSegmentationLevelSetImageFilter::~ThresholdSegmentationLevelSetImageFilter "
32624
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter "
32626
An inverse deconvolution filter regularized in the Tikhonov sense.
32629
The Tikhonov deconvolution filter is the inverse deconvolution filter
32630
with a regularization term added to the denominator. The filter
32631
minimizes the equation \\\\[ ||\\\\hat{f} \\\\otimes h - g||_{L_2}^2 + \\\\mu||\\\\hat{f}||^2
32632
\\\\] where $\\\\hat{f}$ is the estimate of the unblurred image, $h$ is the blurring kernel, $g$ is the blurred image, and $\\\\mu$ is a non-negative real regularization function.
32634
The filter applies a kernel described in the Fourier domain as $H^*(\\\\omega) / (|H(\\\\omega)|^2 + \\\\mu)$ where $H(\\\\omega)$ is the Fourier transform of $h$ . The term $\\\\mu$ is called RegularizationConstant in this filter. If $\\\\mu$ is set to zero, this filter is equivalent to the InverseDeconvolutionImageFilter .
32637
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
32638
de Jouy-en-Josas, France
32639
Cory Quammen, The University of North Carolina at Chapel Hill
32641
itk::simple::TikhonovDeconvolution for the procedural interface
32643
itk::TikhonovDeconvolutionImageFilter for the Doxygen on the original ITK class.
32646
C++ includes: sitkTikhonovDeconvolutionImageFilter.h
32649
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::Execute "
32651
Execute the filter on the input images
32655
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::Execute "
32657
Execute the filter on the input images with the given parameters
32661
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::GetBoundaryCondition "
32664
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::GetName "
32670
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::GetNormalize "
32673
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::GetOutputRegionMode "
32676
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::GetRegularizationConstant "
32678
The regularization factor. Larger values reduce the dominance of noise
32679
in the solution, but results in higher approximation error in the
32680
deblurred image. Default value is 0.0, yielding the same results as
32681
the InverseDeconvolutionImageFilter .
32685
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::NormalizeOff "
32688
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::NormalizeOn "
32690
Set the value of Normalize to true or false respectfully.
32694
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::SetBoundaryCondition "
32697
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::SetNormalize "
32699
Normalize the output image by the sum of the kernel components
32703
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::SetOutputRegionMode "
32706
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::SetRegularizationConstant "
32708
The regularization factor. Larger values reduce the dominance of noise
32709
in the solution, but results in higher approximation error in the
32710
deblurred image. Default value is 0.0, yielding the same results as
32711
the InverseDeconvolutionImageFilter .
32715
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::TikhonovDeconvolutionImageFilter "
32717
Default Constructor that takes no arguments and initializes default
32722
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::ToString "
32724
Print ourselves out
32728
%feature("docstring") itk::simple::TikhonovDeconvolutionImageFilter::~TikhonovDeconvolutionImageFilter "
32735
%feature("docstring") itk::simple::TileImageFilter "
32737
Tile multiple input images into a single output image.
32740
This filter will tile multiple images using a user-specified layout.
32741
The tile sizes will be large enough to accommodate the largest image
32742
for each tile. The layout is specified with the SetLayout method. The
32743
layout has the same dimension as the output image. If all entries of
32744
the layout are positive, the tiled output will contain the exact
32745
number of tiles. If the layout contains a 0 in the last dimension, the
32746
filter will compute a size that will accommodate all of the images.
32747
Empty tiles are filled with the value specified with the SetDefault
32748
value method. The input images must have a dimension less than or
32749
equal to the output image. The output image have a larger dimension
32750
than the input images. This filter can be used to create a volume from
32751
a series of inputs by specifying a layout of 1,1,0.
32757
Tile multiple images into another image
32759
Stack multiple 2D images into a 3D image
32761
Tile multiple images side by side
32764
itk::simple::Tile for the procedural interface
32767
C++ includes: sitkTileImageFilter.h
32770
%feature("docstring") itk::simple::TileImageFilter::Execute "
32772
Execute the filter on the input images
32776
%feature("docstring") itk::simple::TileImageFilter::Execute "
32779
%feature("docstring") itk::simple::TileImageFilter::Execute "
32782
%feature("docstring") itk::simple::TileImageFilter::Execute "
32785
%feature("docstring") itk::simple::TileImageFilter::Execute "
32788
%feature("docstring") itk::simple::TileImageFilter::Execute "
32791
%feature("docstring") itk::simple::TileImageFilter::Execute "
32793
Execute the filter on the input images with the given parameters
32797
%feature("docstring") itk::simple::TileImageFilter::Execute "
32800
%feature("docstring") itk::simple::TileImageFilter::Execute "
32803
%feature("docstring") itk::simple::TileImageFilter::Execute "
32806
%feature("docstring") itk::simple::TileImageFilter::Execute "
32809
%feature("docstring") itk::simple::TileImageFilter::Execute "
32812
%feature("docstring") itk::simple::TileImageFilter::GetDefaultPixelValue "
32815
%feature("docstring") itk::simple::TileImageFilter::GetLayout "
32818
%feature("docstring") itk::simple::TileImageFilter::GetName "
32824
%feature("docstring") itk::simple::TileImageFilter::SetDefaultPixelValue "
32827
%feature("docstring") itk::simple::TileImageFilter::SetLayout "
32830
%feature("docstring") itk::simple::TileImageFilter::TileImageFilter "
32832
Default Constructor that takes no arguments and initializes default
32837
%feature("docstring") itk::simple::TileImageFilter::ToString "
32839
Print ourselves out
32843
%feature("docstring") itk::simple::TileImageFilter::~TileImageFilter "
32850
%feature("docstring") itk::simple::Transform "
32852
A simplified wrapper around a variety of ITK transforms.
32855
The interface to ITK transform objects to be used with the ImageRegistrationMethod, ResampleImageFilter and other SimpleITK process objects. The transforms are designed to
32856
have a serialized array of parameters to facilitate optimization for
32859
Provides a base class interface to any type of ITK transform. Objects
32860
of this type may have their interface converted to a derived interface
32861
while keeping the same reference to the ITK object.
32863
Additionally, this class provides a basic interface to a composite
32868
itk::CompositeTransform
32871
C++ includes: sitkTransform.h
32874
%feature("docstring") itk::simple::Transform::AddTransform "
32877
%feature("docstring") itk::simple::Transform::GetDimension "
32879
Return the dimension of the Transform ( 2D or 3D )
32883
%feature("docstring") itk::simple::Transform::GetInverse "
32885
Return a new inverse transform of the same type as this.
32888
Creates a new transform object and tries to set the value to the
32889
inverse. As not all transform types have inverse and some transforms
32890
are not invertable, an exception will be throw is there is no inverse.
32894
%feature("docstring") itk::simple::Transform::GetName "
32896
return user readable name for the SimpleITK transform
32900
%feature("docstring") itk::simple::Transform::IsLinear "
32903
%feature("docstring") itk::simple::Transform::MakeUnique "
32905
Performs actually coping if needed to make object unique.
32908
The Transform class by default performs lazy coping and assignment. This method
32909
make sure that coping actually happens to the itk::Transform pointed to is only pointed to by this object.
32913
%feature("docstring") itk::simple::Transform::SetIdentity "
32916
%feature("docstring") itk::simple::Transform::SetInverse "
32918
Try to change the current transform to it's inverse.
32921
If the transform has an inverse, i.e. non-singular linear transforms,
32922
then a new ITK transform is created of the same type and this object
32925
However not all transform have a direct inverse, if the inverse does
32926
not exist or fails false will be returned and this transform will not
32931
%feature("docstring") itk::simple::Transform::ToString "
32934
%feature("docstring") itk::simple::Transform::Transform "
32936
By default a 3-d identity transform is constructed.
32940
%feature("docstring") itk::simple::Transform::Transform "
32942
Construct a SimpleITK Transform from a pointer to an ITK composite transform.
32946
%feature("docstring") itk::simple::Transform::Transform "
32949
%feature("docstring") itk::simple::Transform::Transform "
32951
Construct a specific transformation.
32955
This constructor will be removed in future releases.
32960
%feature("docstring") itk::simple::Transform::Transform "
32962
Use an image to construct a transform.
32965
The input displacement image is transferred to the constructed
32966
transform object. The input image is modified to be a default
32967
constructed Image object.
32969
Only the sitkDisplacementField transformation type can currently be
32970
constructed this way. Image must be of sitkVectorFloat64 pixel type with the number of components
32971
equal to the image dimension.
32974
This constructor will be removed in future releases.
32979
%feature("docstring") itk::simple::Transform::TransformPoint "
32982
%feature("docstring") itk::simple::Transform::WriteTransform "
32985
%feature("docstring") itk::simple::Transform::~Transform "
32989
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter "
32991
Generate a displacement field from a coordinate transform.
32994
Output information (spacing, size and direction) for the output image
32995
should be set. This information has the normal defaults of unit
32996
spacing, zero origin and identity direction. Optionally, the output
32997
information can be obtained from a reference image. If the reference
32998
image is provided and UseReferenceImage is On, then the spacing,
32999
origin and direction of the reference image will be used.
33001
Since this filter produces an image which is a different size than its
33002
input, it needs to override several of the methods defined in ProcessObject in order to properly manage the pipeline execution model. In
33003
particular, this filter overrides
33004
ProcessObject::GenerateOutputInformation() .
33006
This filter is implemented as a multithreaded filter. It provides a
33007
ThreadedGenerateData() method for its implementation.
33010
Marius Staring, Leiden University Medical Center, The Netherlands.
33011
This class was taken from the Insight Journal paper: https://hdl.handle.net/1926/1387
33013
itk::simple::TransformToDisplacementFieldFilter for the procedural interface
33015
itk::TransformToDisplacementFieldFilter for the Doxygen on the original ITK class.
33018
C++ includes: sitkTransformToDisplacementFieldFilter.h
33021
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::Execute "
33023
Execute the filter on the input image
33027
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::Execute "
33029
Execute the filter on the input image with the given parameters
33033
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetName "
33039
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetOutputDirection "
33041
Set the output direction cosine matrix.
33045
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetOutputOrigin "
33047
Get the output image origin.
33051
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetOutputPixelType "
33053
Get the ouput pixel type.
33057
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetOutputSpacing "
33059
Get the output image spacing.
33063
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::GetSize "
33065
Set/Get the size of the output image.
33069
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetOutputDirection "
33071
Set the output direction cosine matrix.
33075
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetOutputOrigin "
33077
Set the output image origin.
33081
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetOutputPixelType "
33083
Set the output pixel type, only sitkVectorFloat32 and
33084
sitkVectorFloat64 are supported.
33088
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetOutputSpacing "
33090
Set the output image spacing.
33094
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetReferenceImage "
33096
This methods sets the size, origin, spacing and direction to that of
33101
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::SetSize "
33103
Set/Get the size of the output image.
33107
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::ToString "
33109
Print ourselves out
33113
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::TransformToDisplacementFieldFilter "
33115
Default Constructor that takes no arguments and initializes default
33120
%feature("docstring") itk::simple::TransformToDisplacementFieldFilter::~TransformToDisplacementFieldFilter "
33127
%feature("docstring") itk::simple::TranslationTransform "
33129
Translation of a 2D or 3D coordinate space.
33134
itk::TranslationTransform
33137
C++ includes: sitkTranslationTransform.h
33140
%feature("docstring") itk::simple::TranslationTransform::GetOffset "
33143
%feature("docstring") itk::simple::TranslationTransform::SetOffset "
33146
%feature("docstring") itk::simple::TranslationTransform::TranslationTransform "
33149
%feature("docstring") itk::simple::TranslationTransform::TranslationTransform "
33152
%feature("docstring") itk::simple::TranslationTransform::TranslationTransform "
33156
%feature("docstring") itk::simple::TriangleThresholdImageFilter "
33158
Threshold an image using the Triangle Threshold.
33161
This filter creates a binary thresholded image that separates an image
33162
into foreground and background components. The filter computes the
33163
threshold using the TriangleThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
33166
Richard Beare. Department of Medicine, Monash University, Melbourne,
33168
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
33169
de Jouy-en-Josas, France.
33171
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
33175
HistogramThresholdImageFilter
33177
itk::simple::TriangleThreshold for the procedural interface
33179
itk::TriangleThresholdImageFilter for the Doxygen on the original ITK class.
33182
C++ includes: sitkTriangleThresholdImageFilter.h
33185
%feature("docstring") itk::simple::TriangleThresholdImageFilter::Execute "
33187
Execute the filter on the input image
33191
%feature("docstring") itk::simple::TriangleThresholdImageFilter::Execute "
33194
%feature("docstring") itk::simple::TriangleThresholdImageFilter::Execute "
33196
Execute the filter on the input image with the given parameters
33200
%feature("docstring") itk::simple::TriangleThresholdImageFilter::Execute "
33203
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetInsideValue "
33205
Get the \"inside\" pixel value.
33209
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetMaskOutput "
33212
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetMaskValue "
33215
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetName "
33221
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetNumberOfHistogramBins "
33224
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetOutsideValue "
33226
Get the \"outside\" pixel value.
33230
%feature("docstring") itk::simple::TriangleThresholdImageFilter::GetThreshold "
33232
Get the computed threshold.
33235
This is a measurement. Its value is updated in the Execute methods, so
33236
the value will only be valid after an execution.
33240
%feature("docstring") itk::simple::TriangleThresholdImageFilter::MaskOutputOff "
33243
%feature("docstring") itk::simple::TriangleThresholdImageFilter::MaskOutputOn "
33245
Set the value of MaskOutput to true or false respectfully.
33249
%feature("docstring") itk::simple::TriangleThresholdImageFilter::SetInsideValue "
33251
Set the \"inside\" pixel value.
33255
%feature("docstring") itk::simple::TriangleThresholdImageFilter::SetMaskOutput "
33257
Do you want the output to be masked by the mask used in histogram
33258
construction. Only relevant if masking is in use.
33262
%feature("docstring") itk::simple::TriangleThresholdImageFilter::SetMaskValue "
33264
The value in the mask image, if used, indicating voxels that should be
33265
included. Default is the max of pixel type, as in the
33266
MaskedImageToHistogramFilter
33270
%feature("docstring") itk::simple::TriangleThresholdImageFilter::SetNumberOfHistogramBins "
33272
Set/Get the number of histogram bins.
33276
%feature("docstring") itk::simple::TriangleThresholdImageFilter::SetOutsideValue "
33278
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
33282
%feature("docstring") itk::simple::TriangleThresholdImageFilter::ToString "
33284
Print ourselves out
33288
%feature("docstring") itk::simple::TriangleThresholdImageFilter::TriangleThresholdImageFilter "
33290
Default Constructor that takes no arguments and initializes default
33295
%feature("docstring") itk::simple::TriangleThresholdImageFilter::~TriangleThresholdImageFilter "
33302
%feature("docstring") itk::simple::UnaryMinusImageFilter "
33304
Computes the negative of each pixel.
33309
itk::simple::UnaryMinus for the procedural interface
33311
itk::UnaryFunctorImageFilter for the Doxygen on the original ITK class.
33314
C++ includes: sitkUnaryMinusImageFilter.h
33317
%feature("docstring") itk::simple::UnaryMinusImageFilter::Execute "
33319
Execute the filter on the input image
33323
%feature("docstring") itk::simple::UnaryMinusImageFilter::GetName "
33329
%feature("docstring") itk::simple::UnaryMinusImageFilter::ToString "
33331
Print ourselves out
33335
%feature("docstring") itk::simple::UnaryMinusImageFilter::UnaryMinusImageFilter "
33337
Default Constructor that takes no arguments and initializes default
33342
%feature("docstring") itk::simple::UnaryMinusImageFilter::~UnaryMinusImageFilter "
33349
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter "
33351
Transforms the image so that any pixel that is not a regional maxima
33352
is set to the minimum value for the pixel type. Pixels that are
33353
regional maxima retain their value.
33356
Regional maxima are flat zones surrounded by pixels of lower value. A
33357
completely flat image will be marked as a regional maxima by this
33360
This code was contributed in the Insight Journal paper: \"Finding
33361
regional extrema - methods and performance\" by Beare R., Lehmann G. https://hdl.handle.net/1926/153 http://www.insight-journal.org/browse/publication/65
33364
Richard Beare. Department of Medicine, Monash University, Melbourne,
33368
ValuedRegionalMinimaImageFilter
33370
ValuedRegionalExtremaImageFilter
33377
ValuedRegionalMaximaImageFilter
33379
itk::simple::ValuedRegionalMaxima for the procedural interface
33381
itk::ValuedRegionalMaximaImageFilter for the Doxygen on the original ITK class.
33385
C++ includes: sitkValuedRegionalMaximaImageFilter.h
33388
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::Execute "
33390
Execute the filter on the input image
33394
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::Execute "
33396
Execute the filter on the input image with the given parameters
33400
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::FullyConnectedOff "
33403
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::FullyConnectedOn "
33405
Set the value of FullyConnected to true or false respectfully.
33409
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::GetFlat "
33411
This is a measurement. Its value is updated in the Execute methods, so
33412
the value will only be valid after an execution.
33416
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::GetFullyConnected "
33419
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::GetName "
33425
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::SetFullyConnected "
33428
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::ToString "
33430
Print ourselves out
33434
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::ValuedRegionalMaximaImageFilter "
33436
Default Constructor that takes no arguments and initializes default
33441
%feature("docstring") itk::simple::ValuedRegionalMaximaImageFilter::~ValuedRegionalMaximaImageFilter "
33448
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter "
33450
Transforms the image so that any pixel that is not a regional minima
33451
is set to the maximum value for the pixel type. Pixels that are
33452
regional minima retain their value.
33455
Regional minima are flat zones surrounded by pixels of higher value. A
33456
completely flat image will be marked as a regional minima by this
33459
This code was contributed in the Insight Journal paper: \"Finding
33460
regional extrema - methods and performance\" by Beare R., Lehmann G. https://hdl.handle.net/1926/153 http://www.insight-journal.org/browse/publication/65
33463
Richard Beare. Department of Medicine, Monash University, Melbourne,
33467
ValuedRegionalMaximaImageFilter , ValuedRegionalExtremaImageFilter ,
33474
ValuedRegionalMinimaImageFilter
33476
itk::simple::ValuedRegionalMinima for the procedural interface
33478
itk::ValuedRegionalMinimaImageFilter for the Doxygen on the original ITK class.
33482
C++ includes: sitkValuedRegionalMinimaImageFilter.h
33485
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::Execute "
33487
Execute the filter on the input image
33491
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::Execute "
33493
Execute the filter on the input image with the given parameters
33497
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::FullyConnectedOff "
33500
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::FullyConnectedOn "
33502
Set the value of FullyConnected to true or false respectfully.
33506
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::GetFlat "
33508
This is a measurement. Its value is updated in the Execute methods, so
33509
the value will only be valid after an execution.
33513
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::GetFullyConnected "
33516
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::GetName "
33522
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::SetFullyConnected "
33525
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::ToString "
33527
Print ourselves out
33531
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::ValuedRegionalMinimaImageFilter "
33533
Default Constructor that takes no arguments and initializes default
33538
%feature("docstring") itk::simple::ValuedRegionalMinimaImageFilter::~ValuedRegionalMinimaImageFilter "
33545
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter "
33547
Segment pixels with similar statistics using connectivity.
33550
This filter extracts a connected set of pixels whose pixel intensities
33551
are consistent with the pixel statistics of a seed point. The mean and
33552
variance across a neighborhood (8-connected, 26-connected, etc.) are
33553
calculated for a seed point. Then pixels connected to this seed point
33554
whose values are within the confidence interval for the seed point are
33555
grouped. The width of the confidence interval is controlled by the
33556
\"Multiplier\" variable (the confidence interval is the mean plus or
33557
minus the \"Multiplier\" times the standard deviation). If the
33558
intensity variations across a segment were gaussian, a \"Multiplier\"
33559
setting of 2.5 would define a confidence interval wide enough to
33560
capture 99% of samples in the segment.
33562
After this initial segmentation is calculated, the mean and variance
33563
are re-calculated. All the pixels in the previous segmentation are
33564
used to calculate the mean the standard deviation (as opposed to using
33565
the pixels in the neighborhood of the seed point). The segmentation is
33566
then recalculted using these refined estimates for the mean and
33567
variance of the pixel values. This process is repeated for the
33568
specified number of iterations. Setting the \"NumberOfIterations\" to
33569
zero stops the algorithm after the initial segmentation from the seed
33572
NOTE: the lower and upper threshold are restricted to lie within the
33573
valid numeric limits of the input data pixel type. Also, the limits
33574
may be adjusted to contain the seed point's intensity.
33576
itk::simple::VectorConfidenceConnected for the procedural interface
33578
itk::VectorConfidenceConnectedImageFilter for the Doxygen on the original ITK class.
33581
C++ includes: sitkVectorConfidenceConnectedImageFilter.h
33584
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::AddSeed "
33586
AddSeed - Add a seed to the end of the list
33590
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::ClearSeeds "
33592
ClearSeeds - Clear out all seeds in the list
33596
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::Execute "
33598
Execute the filter on the input image
33602
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::Execute "
33604
Execute the filter on the input image with the given parameters
33608
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetCovariance "
33610
Get the Covariance matrix computed during the segmentation
33612
This is a measurement. Its value is updated in the Execute methods, so
33613
the value will only be valid after an execution.
33617
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetInitialNeighborhoodRadius "
33619
Get/Set the radius of the neighborhood over which the statistics are
33624
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetMean "
33626
Get the Mean Vector computed during the segmentation
33628
This is a measurement. Its value is updated in the Execute methods, so
33629
the value will only be valid after an execution.
33633
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetMultiplier "
33635
Set/Get the multiplier to define the confidence interval. Multiplier
33636
can be anything greater than zero. A typical value is 2.5
33640
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetName "
33646
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetNumberOfIterations "
33648
Set/Get the number of iterations
33652
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetReplaceValue "
33654
Set/Get value to replace thresholded pixels
33658
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::GetSeedList "
33664
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetInitialNeighborhoodRadius "
33666
Get/Set the radius of the neighborhood over which the statistics are
33671
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetMultiplier "
33673
Set/Get the multiplier to define the confidence interval. Multiplier
33674
can be anything greater than zero. A typical value is 2.5
33678
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetNumberOfIterations "
33680
Set/Get the number of iterations
33684
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetReplaceValue "
33686
Set/Get value to replace thresholded pixels
33690
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetSeed "
33692
SetSeed - Set list to a single seed
33696
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::SetSeedList "
33702
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::ToString "
33704
Print ourselves out
33708
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::VectorConfidenceConnectedImageFilter "
33710
Default Constructor that takes no arguments and initializes default
33715
%feature("docstring") itk::simple::VectorConfidenceConnectedImageFilter::~VectorConfidenceConnectedImageFilter "
33722
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter "
33724
A connected components filter that labels the objects in a vector
33725
image. Two vectors are pointing similar directions if one minus their
33726
dot product is less than a threshold. Vectors that are 180 degrees out
33727
of phase are similar. Assumes that vectors are normalized.
33732
itk::simple::VectorConnectedComponent for the procedural interface
33734
itk::VectorConnectedComponentImageFilter for the Doxygen on the original ITK class.
33737
C++ includes: sitkVectorConnectedComponentImageFilter.h
33740
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::Execute "
33742
Execute the filter on the input image
33746
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::Execute "
33748
Execute the filter on the input image with the given parameters
33752
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::FullyConnectedOff "
33755
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::FullyConnectedOn "
33757
Set the value of FullyConnected to true or false respectfully.
33761
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::GetDistanceThreshold "
33764
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::GetFullyConnected "
33767
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::GetName "
33773
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::SetDistanceThreshold "
33776
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::SetFullyConnected "
33779
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::ToString "
33781
Print ourselves out
33785
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::VectorConnectedComponentImageFilter "
33787
Default Constructor that takes no arguments and initializes default
33792
%feature("docstring") itk::simple::VectorConnectedComponentImageFilter::~VectorConnectedComponentImageFilter "
33799
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter "
33801
Extracts the selected index of the vector that is the input pixel
33805
This filter is templated over the input image type and output image
33808
The filter expect the input image pixel type to be a vector and the
33809
output image pixel type to be a scalar. The only requirement on the
33810
type used for representing the vector is that it must provide an
33820
Extract a component/channel of a vector image
33822
itk::simple::VectorIndexSelectionCast for the procedural interface
33824
itk::VectorIndexSelectionCastImageFilter for the Doxygen on the original ITK class.
33828
C++ includes: sitkVectorIndexSelectionCastImageFilter.h
33831
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::Execute "
33833
Execute the filter on the input image
33837
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::Execute "
33839
Execute the filter on the input image with the given parameters
33843
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::GetIndex "
33846
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::GetName "
33852
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::GetOutputPixelType "
33854
Get the ouput pixel type.
33858
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::SetIndex "
33860
Get/Set methods for the index
33864
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::SetOutputPixelType "
33866
Set the output pixel type of the scalar component to extract.
33870
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::ToString "
33872
Print ourselves out
33876
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::VectorIndexSelectionCastImageFilter "
33878
Default Constructor that takes no arguments and initializes default
33883
%feature("docstring") itk::simple::VectorIndexSelectionCastImageFilter::~VectorIndexSelectionCastImageFilter "
33890
%feature("docstring") itk::simple::VectorMagnitudeImageFilter "
33892
Take an image of vectors as input and produce an image with the
33893
magnitude of those vectors.
33896
The filter expects the input image pixel type to be a vector and the
33897
output image pixel type to be a scalar.
33899
This filter assumes that the PixelType of the input image is a
33900
VectorType that provides a GetNorm() method.
33906
Compute the magnitude of each pixel in a vector image to produce a
33909
itk::simple::VectorMagnitude for the procedural interface
33911
itk::VectorMagnitudeImageFilter for the Doxygen on the original ITK class.
33915
C++ includes: sitkVectorMagnitudeImageFilter.h
33918
%feature("docstring") itk::simple::VectorMagnitudeImageFilter::Execute "
33920
Execute the filter on the input image
33924
%feature("docstring") itk::simple::VectorMagnitudeImageFilter::GetName "
33930
%feature("docstring") itk::simple::VectorMagnitudeImageFilter::ToString "
33932
Print ourselves out
33936
%feature("docstring") itk::simple::VectorMagnitudeImageFilter::VectorMagnitudeImageFilter "
33938
Default Constructor that takes no arguments and initializes default
33943
%feature("docstring") itk::simple::VectorMagnitudeImageFilter::~VectorMagnitudeImageFilter "
33950
%feature("docstring") itk::simple::Version "
33952
Version info for SimpleITK.
33954
C++ includes: sitkVersion.h
33957
%feature("docstring") itk::simple::Version::ToString "
33961
%feature("docstring") itk::simple::VersorRigid3DTransform "
33963
A rotation as a versor around a fixed center with translation of a 3D
33969
itk::VersorRigid3DTransform
33972
C++ includes: sitkVersorRigid3DTransform.h
33975
%feature("docstring") itk::simple::VersorRigid3DTransform::GetCenter "
33978
%feature("docstring") itk::simple::VersorRigid3DTransform::GetMatrix "
33981
%feature("docstring") itk::simple::VersorRigid3DTransform::GetTranslation "
33984
%feature("docstring") itk::simple::VersorRigid3DTransform::GetVersor "
33987
%feature("docstring") itk::simple::VersorRigid3DTransform::SetCenter "
33993
%feature("docstring") itk::simple::VersorRigid3DTransform::SetMatrix "
33996
%feature("docstring") itk::simple::VersorRigid3DTransform::SetRotation "
34002
%feature("docstring") itk::simple::VersorRigid3DTransform::SetRotation "
34005
%feature("docstring") itk::simple::VersorRigid3DTransform::SetTranslation "
34008
%feature("docstring") itk::simple::VersorRigid3DTransform::Translate "
34014
%feature("docstring") itk::simple::VersorRigid3DTransform::VersorRigid3DTransform "
34017
%feature("docstring") itk::simple::VersorRigid3DTransform::VersorRigid3DTransform "
34020
%feature("docstring") itk::simple::VersorRigid3DTransform::VersorRigid3DTransform "
34023
%feature("docstring") itk::simple::VersorRigid3DTransform::VersorRigid3DTransform "
34026
%feature("docstring") itk::simple::VersorRigid3DTransform::VersorRigid3DTransform "
34030
%feature("docstring") itk::simple::VersorTransform "
34032
A 3D rotation transform with rotation as a versor around a fixed
34038
itk::VersorTransform
34041
C++ includes: sitkVersorTransform.h
34044
%feature("docstring") itk::simple::VersorTransform::GetCenter "
34047
%feature("docstring") itk::simple::VersorTransform::GetMatrix "
34053
%feature("docstring") itk::simple::VersorTransform::GetVersor "
34056
%feature("docstring") itk::simple::VersorTransform::SetCenter "
34062
%feature("docstring") itk::simple::VersorTransform::SetMatrix "
34065
%feature("docstring") itk::simple::VersorTransform::SetRotation "
34071
%feature("docstring") itk::simple::VersorTransform::SetRotation "
34074
%feature("docstring") itk::simple::VersorTransform::VersorTransform "
34077
%feature("docstring") itk::simple::VersorTransform::VersorTransform "
34080
%feature("docstring") itk::simple::VersorTransform::VersorTransform "
34083
%feature("docstring") itk::simple::VersorTransform::VersorTransform "
34086
%feature("docstring") itk::simple::VersorTransform::VersorTransform "
34090
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter "
34092
Fills in holes and cavities by applying a voting operation on each
34100
VotingBinaryImageFilter
34102
VotingBinaryIterativeHoleFillingImageFilter
34106
NeighborhoodOperator
34108
NeighborhoodIterator
34110
itk::simple::VotingBinaryHoleFilling for the procedural interface
34112
itk::VotingBinaryHoleFillingImageFilter for the Doxygen on the original ITK class.
34115
C++ includes: sitkVotingBinaryHoleFillingImageFilter.h
34118
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::Execute "
34120
Execute the filter on the input image
34124
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::Execute "
34126
Execute the filter on the input image with the given parameters
34130
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::GetBackgroundValue "
34133
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::GetForegroundValue "
34136
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::GetMajorityThreshold "
34138
Majority threshold. It is the number of pixels over 50% that will
34139
decide whether an OFF pixel will become ON or not. For example, if the
34140
neighborhood of a pixel has 124 pixels (excluding itself), the 50%
34141
will be 62, and if you set upd a Majority threshold of 5, that means
34142
that the filter will require 67 or more neighbor pixels to be ON in
34143
order to switch the current OFF pixel to ON. The default value is 1.
34147
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::GetName "
34153
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::GetRadius "
34156
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::SetBackgroundValue "
34159
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::SetForegroundValue "
34162
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::SetMajorityThreshold "
34164
Majority threshold. It is the number of pixels over 50% that will
34165
decide whether an OFF pixel will become ON or not. For example, if the
34166
neighborhood of a pixel has 124 pixels (excluding itself), the 50%
34167
will be 62, and if you set upd a Majority threshold of 5, that means
34168
that the filter will require 67 or more neighbor pixels to be ON in
34169
order to switch the current OFF pixel to ON. The default value is 1.
34173
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::SetRadius "
34176
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::SetRadius "
34178
Set the values of the Radius vector all to value
34182
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::ToString "
34184
Print ourselves out
34188
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::VotingBinaryHoleFillingImageFilter "
34190
Default Constructor that takes no arguments and initializes default
34195
%feature("docstring") itk::simple::VotingBinaryHoleFillingImageFilter::~VotingBinaryHoleFillingImageFilter "
34202
%feature("docstring") itk::simple::VotingBinaryImageFilter "
34204
Applies a voting operation in a neighborhood of each pixel.
34208
Pixels which are not Foreground or Background will remain unchanged.
34215
NeighborhoodOperator
34217
NeighborhoodIterator
34219
itk::simple::VotingBinary for the procedural interface
34221
itk::VotingBinaryImageFilter for the Doxygen on the original ITK class.
34224
C++ includes: sitkVotingBinaryImageFilter.h
34227
%feature("docstring") itk::simple::VotingBinaryImageFilter::Execute "
34229
Execute the filter on the input image
34233
%feature("docstring") itk::simple::VotingBinaryImageFilter::Execute "
34235
Execute the filter on the input image with the given parameters
34239
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetBackgroundValue "
34241
Get the value associated with the Foreground (or the object) on the
34242
binary input image and the Background .
34246
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetBirthThreshold "
34248
Birth threshold. Pixels that are OFF will turn ON when the number of
34249
neighbors ON is larger than the value defined in this threshold.
34253
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetForegroundValue "
34255
Get the value associated with the Foreground (or the object) on the
34256
binary input image and the Background .
34260
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetName "
34266
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetRadius "
34268
Get the radius of the neighborhood used to compute the median
34272
%feature("docstring") itk::simple::VotingBinaryImageFilter::GetSurvivalThreshold "
34274
Survival threshold. Pixels that are ON will turn OFF when the number
34275
of neighbors ON is smaller than the value defined in this survival
34280
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetBackgroundValue "
34282
Set the value associated with the Foreground (or the object) on the
34283
binary input image and the Background .
34287
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetBirthThreshold "
34289
Birth threshold. Pixels that are OFF will turn ON when the number of
34290
neighbors ON is larger than the value defined in this threshold.
34294
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetForegroundValue "
34296
Set the value associated with the Foreground (or the object) on the
34297
binary input image and the Background .
34301
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetRadius "
34303
Set the radius of the neighborhood used to compute the median.
34307
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetRadius "
34309
Set the values of the Radius vector all to value
34313
%feature("docstring") itk::simple::VotingBinaryImageFilter::SetSurvivalThreshold "
34315
Survival threshold. Pixels that are ON will turn OFF when the number
34316
of neighbors ON is smaller than the value defined in this survival
34321
%feature("docstring") itk::simple::VotingBinaryImageFilter::ToString "
34323
Print ourselves out
34327
%feature("docstring") itk::simple::VotingBinaryImageFilter::VotingBinaryImageFilter "
34329
Default Constructor that takes no arguments and initializes default
34334
%feature("docstring") itk::simple::VotingBinaryImageFilter::~VotingBinaryImageFilter "
34341
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter "
34343
Fills in holes and cavities by iteratively applying a voting
34347
This filter uses internally the VotingBinaryHoleFillingImageFilter , and runs it iteratively until no pixels are being changed or until
34348
it reaches the maximum number of iterations. The purpose of the filter
34349
is to fill in holes of medium size (tens of pixels in radius). In
34350
principle the number of iterations is related to the size of the holes
34351
to be filled in. The larger the holes, the more iteration must be run
34352
with this filter in order to fill in the full hole. The size of the
34353
neighborhood is also related to the curvature of the hole borders and
34354
therefore the hole size. Note that as a collateral effect this filter
34355
may also fill in cavities in the external side of structures.
34357
This filter is templated over a single image type because the output
34358
image type must be the same as the input image type. This is required
34359
in order to make the iterations possible, since the output image of
34360
one iteration is taken as the input image for the next iteration.
34366
VotingBinaryImageFilter
34368
VotingBinaryHoleFillingImageFilter
34372
NeighborhoodOperator
34374
NeighborhoodIterator
34376
itk::simple::VotingBinaryIterativeHoleFilling for the procedural interface
34378
itk::VotingBinaryIterativeHoleFillingImageFilter for the Doxygen on the original ITK class.
34381
C++ includes: sitkVotingBinaryIterativeHoleFillingImageFilter.h
34384
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::Execute "
34386
Execute the filter on the input image
34390
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::Execute "
34392
Execute the filter on the input image with the given parameters
34396
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetBackgroundValue "
34398
Get the value associated with the Foreground (or the object) on the
34399
binary input image and the Background .
34403
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetForegroundValue "
34405
Get the value associated with the Foreground (or the object) on the
34406
binary input image and the Background .
34410
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetMajorityThreshold "
34412
Majority threshold. It is the number of pixels over 50% that will
34413
decide whether an OFF pixel will become ON or not. For example, if the
34414
neighborhood of a pixel has 124 pixels (excluding itself), the 50%
34415
will be 62, and if you set upd a Majority threshold of 5, that means
34416
that the filter will require 67 or more neighbor pixels to be ON in
34417
order to switch the current OFF pixel to ON. The default value is 1.
34421
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetMaximumNumberOfIterations "
34423
Maximum number of iterations. This filter is executed iteratively as
34424
long as at least one pixel has changed in a previous iteration, or
34425
until the maximum number of iterations has been reached.
34429
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetName "
34435
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::GetRadius "
34437
Get the radius of the neighborhood used to compute the median
34441
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetBackgroundValue "
34443
Set the value associated with the Foreground (or the object) on the
34444
binary input image and the Background .
34448
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetForegroundValue "
34450
Set the value associated with the Foreground (or the object) on the
34451
binary input image and the Background .
34455
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetMajorityThreshold "
34457
Majority threshold. It is the number of pixels over 50% that will
34458
decide whether an OFF pixel will become ON or not. For example, if the
34459
neighborhood of a pixel has 124 pixels (excluding itself), the 50%
34460
will be 62, and if you set upd a Majority threshold of 5, that means
34461
that the filter will require 67 or more neighbor pixels to be ON in
34462
order to switch the current OFF pixel to ON. The default value is 1.
34466
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetMaximumNumberOfIterations "
34468
Maximum number of iterations. This filter is executed iteratively as
34469
long as at least one pixel has changed in a previous iteration, or
34470
until the maximum number of iterations has been reached.
34474
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetRadius "
34476
Set the radius of the neighborhood used to compute the median.
34480
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::SetRadius "
34482
Set the values of the Radius vector all to value
34486
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::ToString "
34488
Print ourselves out
34492
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::VotingBinaryIterativeHoleFillingImageFilter "
34494
Default Constructor that takes no arguments and initializes default
34499
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFillingImageFilter::~VotingBinaryIterativeHoleFillingImageFilter "
34506
%feature("docstring") itk::simple::WarpImageFilter "
34508
Warps an image using an input displacement field.
34511
WarpImageFilter warps an existing image with respect to a given displacement field.
34513
A displacement field is represented as a image whose pixel type is
34514
some vector type with at least N elements, where N is the dimension of
34515
the input image. The vector type must support element access via
34518
The output image is produced by inverse mapping: the output pixels are
34519
mapped back onto the input image. This scheme avoids the creation of
34520
any holes and overlaps in the output image.
34522
Each vector in the displacement field represent the distance between a
34523
geometric point in the input space and a point in the output space
34526
\\\\[ p_{in} = p_{out} + d \\\\]
34528
Typically the mapped position does not correspond to an integer pixel
34529
position in the input image. Interpolation via an image function is
34530
used to compute values at non-integer positions. The default
34531
interpolation typed used is the LinearInterpolateImageFunction . The user can specify a particular interpolation function via SetInterpolator() . Note that the input interpolator must derive from base class InterpolateImageFunction .
34533
Position mapped to outside of the input image buffer are assigned a
34534
edge padding value.
34536
The LargetPossibleRegion for the output is inherited from the input
34537
displacement field. The output image spacing, origin and orientation
34538
may be set via SetOutputSpacing, SetOutputOrigin and
34539
SetOutputDirection. The default are respectively a vector of 1's, a
34540
vector of 0's and an identity matrix.
34542
This class is templated over the type of the input image, the type of
34543
the output image and the type of the displacement field.
34545
The input image is set via SetInput. The input displacement field is
34546
set via SetDisplacementField.
34548
This filter is implemented as a multithreaded filter.
34552
This filter assumes that the input type, output type and displacement
34553
field type all have the same number of dimensions.
34558
Warp one image to another using manually specified landmarks
34560
itk::simple::Warp for the procedural interface
34562
itk::WarpImageFilter for the Doxygen on the original ITK class.
34566
C++ includes: sitkWarpImageFilter.h
34569
%feature("docstring") itk::simple::WarpImageFilter::Execute "
34571
Execute the filter on the input images
34575
%feature("docstring") itk::simple::WarpImageFilter::Execute "
34577
Execute the filter on the input images with the given parameters
34581
%feature("docstring") itk::simple::WarpImageFilter::GetEdgePaddingValue "
34583
Get the edge padding value
34587
%feature("docstring") itk::simple::WarpImageFilter::GetInterpolator "
34589
Get/Set the interpolator function.
34593
%feature("docstring") itk::simple::WarpImageFilter::GetName "
34599
%feature("docstring") itk::simple::WarpImageFilter::GetOutputDirection "
34601
Set/Get the direction (orientation) of the output image
34605
%feature("docstring") itk::simple::WarpImageFilter::GetOutputOrigin "
34607
Get the output image origin.
34611
%feature("docstring") itk::simple::WarpImageFilter::GetOutputSize "
34613
Get the size of the output image.
34617
%feature("docstring") itk::simple::WarpImageFilter::GetOutputSpacing "
34619
Get the output image spacing.
34623
%feature("docstring") itk::simple::WarpImageFilter::SetEdgePaddingValue "
34625
Set the edge padding value
34629
%feature("docstring") itk::simple::WarpImageFilter::SetInterpolator "
34631
Get/Set the interpolator function.
34635
%feature("docstring") itk::simple::WarpImageFilter::SetOutputDirection "
34637
Set/Get the direction (orientation) of the output image
34641
%feature("docstring") itk::simple::WarpImageFilter::SetOutputOrigin "
34643
Set the output image origin.
34647
%feature("docstring") itk::simple::WarpImageFilter::SetOutputParameteresFromImage "
34649
This methods sets the output size, origin, spacing and direction to
34650
that of the provided image
34654
%feature("docstring") itk::simple::WarpImageFilter::SetOutputSize "
34656
Set the size of the output image.
34660
%feature("docstring") itk::simple::WarpImageFilter::SetOutputSpacing "
34662
Set the output image spacing.
34666
%feature("docstring") itk::simple::WarpImageFilter::ToString "
34668
Print ourselves out
34672
%feature("docstring") itk::simple::WarpImageFilter::WarpImageFilter "
34674
Default Constructor that takes no arguments and initializes default
34679
%feature("docstring") itk::simple::WarpImageFilter::~WarpImageFilter "
34686
%feature("docstring") itk::simple::WhiteTopHatImageFilter "
34688
White top hat extracts local maxima that are larger than the
34689
structuring element.
34692
Top-hats are described in Chapter 4.5 of Pierre Soille's book
34693
\"Morphological Image Analysis: Principles and Applications\", Second
34694
Edition, Springer, 2003.
34697
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
34698
de Jouy-en-Josas, France.
34701
itk::simple::WhiteTopHat for the procedural interface
34703
itk::WhiteTopHatImageFilter for the Doxygen on the original ITK class.
34706
C++ includes: sitkWhiteTopHatImageFilter.h
34709
%feature("docstring") itk::simple::WhiteTopHatImageFilter::Execute "
34711
Execute the filter on the input image
34715
%feature("docstring") itk::simple::WhiteTopHatImageFilter::Execute "
34717
Execute the filter on the input image with the given parameters
34721
%feature("docstring") itk::simple::WhiteTopHatImageFilter::GetKernelRadius "
34724
%feature("docstring") itk::simple::WhiteTopHatImageFilter::GetKernelType "
34727
%feature("docstring") itk::simple::WhiteTopHatImageFilter::GetName "
34733
%feature("docstring") itk::simple::WhiteTopHatImageFilter::GetSafeBorder "
34735
A safe border is added to input image to avoid borders effects and
34736
remove it once the closing is done
34740
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SafeBorderOff "
34743
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SafeBorderOn "
34745
Set the value of SafeBorder to true or false respectfully.
34749
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SetKernelRadius "
34751
Kernel radius as a scale for isotropic structures
34755
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SetKernelRadius "
34757
Set/Get the radius of the kernel structuring element as a vector.
34759
If the dimension of the image is greater then the length of r, then
34760
the radius will be padded. If it is less the r will be truncated.
34764
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SetKernelType "
34766
Set/Get the kernel or structuring elemenent used for the morphology
34770
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SetKernelType "
34773
%feature("docstring") itk::simple::WhiteTopHatImageFilter::SetSafeBorder "
34775
A safe border is added to input image to avoid borders effects and
34776
remove it once the closing is done
34780
%feature("docstring") itk::simple::WhiteTopHatImageFilter::ToString "
34782
Print ourselves out
34786
%feature("docstring") itk::simple::WhiteTopHatImageFilter::WhiteTopHatImageFilter "
34788
Default Constructor that takes no arguments and initializes default
34793
%feature("docstring") itk::simple::WhiteTopHatImageFilter::~WhiteTopHatImageFilter "
34800
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter "
34802
The Wiener deconvolution image filter is designed to restore an image
34803
convolved with a blurring kernel while keeping noise enhancement to a
34807
The Wiener filter aims to minimize noise enhancement induced by
34808
frequencies with low signal-to-noise ratio. The Wiener filter kernel
34809
is defined in the frequency domain as $W(\\\\omega) = H^*(\\\\omega) / (|H(\\\\omega)|^2 + (1 /
34810
SNR(\\\\omega)))$ where $H(\\\\omega)$ is the Fourier transform of the blurring kernel with which the
34811
original image was convolved and the signal-to-noise ratio $SNR(\\\\omega)$ . $SNR(\\\\omega)$ is defined by $P_f(\\\\omega) / P_n(\\\\omega)$ where $P_f(\\\\omega)$ is the power spectral density of the uncorrupted signal and $P_n(\\\\omega)$ is the power spectral density of the noise. When applied to the input
34812
blurred image, this filter produces an estimate $\\\\hat{f}(x)$ of the true underlying signal $f(x)$ that minimizes the expected error between $\\\\hat{f}(x)$ and $f(x)$ .
34814
This filter requires two inputs, the image to be deconvolved and the
34815
blurring kernel. These two inputs can be set using the methods
34816
SetInput() and SetKernelImage() , respectively.
34818
The power spectral densities of the signal and noise are typically
34819
unavailable for a given problem. In particular, $P_f(\\\\omega)$ cannot be computed from $f(x)$ because this unknown signal is precisely the signal that this filter
34820
aims to recover. Nevertheless, it is common for the noise to have a
34821
power spectral density that is flat or decreasing significantly more
34822
slowly than the power spectral density of a typical image as the
34823
frequency $\\\\omega$ increases. Hence, $P_n(\\\\omega)$ can typically be approximated with a constant, and this filter makes
34824
this assumption (see the NoiseVariance member variable). $P_f(\\\\omega)$ , on the other hand, will vary with input. This filter computes the
34825
power spectral density of the input blurred image, subtracts the power
34826
spectral density of the noise, and uses the result as the estimate of $P_f(\\\\omega)$ .
34828
For further information on the Wiener deconvolution filter, please see
34829
\"Digital Signal Processing\" by Kenneth R. Castleman, Prentice Hall,
34833
Gaetan Lehmann, Biologie du Developpement et de la Reproduction, INRA
34834
de Jouy-en-Josas, France
34835
Chris Mullins, The University of North Carolina at Chapel Hill
34837
Cory Quammen, The University of North Carolina at Chapel Hill
34839
itk::simple::WienerDeconvolution for the procedural interface
34841
itk::WienerDeconvolutionImageFilter for the Doxygen on the original ITK class.
34844
C++ includes: sitkWienerDeconvolutionImageFilter.h
34847
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::Execute "
34849
Execute the filter on the input images
34853
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::Execute "
34855
Execute the filter on the input images with the given parameters
34859
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::GetBoundaryCondition "
34862
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::GetName "
34868
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::GetNoiseVariance "
34870
Set/get the variance of the zero-mean Gaussian white noise assumed to
34871
be added to the input.
34875
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::GetNormalize "
34878
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::GetOutputRegionMode "
34881
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::NormalizeOff "
34884
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::NormalizeOn "
34886
Set the value of Normalize to true or false respectfully.
34890
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::SetBoundaryCondition "
34893
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::SetNoiseVariance "
34895
Set/get the variance of the zero-mean Gaussian white noise assumed to
34896
be added to the input.
34900
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::SetNormalize "
34902
Normalize the output image by the sum of the kernel components
34906
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::SetOutputRegionMode "
34909
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::ToString "
34911
Print ourselves out
34915
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::WienerDeconvolutionImageFilter "
34917
Default Constructor that takes no arguments and initializes default
34922
%feature("docstring") itk::simple::WienerDeconvolutionImageFilter::~WienerDeconvolutionImageFilter "
34929
%feature("docstring") itk::simple::WrapPadImageFilter "
34931
Increase the image size by padding with replicants of the input image
34935
WrapPadImageFilter changes the image bounds of an image. Added pixels are filled in with
34936
a wrapped replica of the input image. For instance, if the output
34937
image needs a pixel that is two pixels to the left of the
34938
LargestPossibleRegion of the input image, the value assigned will be
34939
from the pixel two pixels inside the right boundary of the
34940
LargestPossibleRegion. The image bounds of the output must be
34943
Visual explanation of padding regions. This filter is implemented as a
34944
multithreaded filter. It provides a ThreadedGenerateData() method for
34945
its implementation.
34949
MirrorPadImageFilter , ConstantPadImageFilter
34954
Pad an image by wrapping
34956
itk::simple::WrapPad for the procedural interface
34958
itk::WrapPadImageFilter for the Doxygen on the original ITK class.
34962
C++ includes: sitkWrapPadImageFilter.h
34965
%feature("docstring") itk::simple::WrapPadImageFilter::Execute "
34967
Execute the filter on the input image
34971
%feature("docstring") itk::simple::WrapPadImageFilter::Execute "
34973
Execute the filter on the input image with the given parameters
34977
%feature("docstring") itk::simple::WrapPadImageFilter::GetName "
34983
%feature("docstring") itk::simple::WrapPadImageFilter::GetPadLowerBound "
34986
%feature("docstring") itk::simple::WrapPadImageFilter::GetPadUpperBound "
34989
%feature("docstring") itk::simple::WrapPadImageFilter::SetPadLowerBound "
34992
%feature("docstring") itk::simple::WrapPadImageFilter::SetPadUpperBound "
34995
%feature("docstring") itk::simple::WrapPadImageFilter::ToString "
34997
Print ourselves out
35001
%feature("docstring") itk::simple::WrapPadImageFilter::WrapPadImageFilter "
35003
Default Constructor that takes no arguments and initializes default
35008
%feature("docstring") itk::simple::WrapPadImageFilter::~WrapPadImageFilter "
35015
%feature("docstring") itk::simple::XorImageFilter "
35017
Computes the XOR bitwise operator pixel-wise between two images.
35020
This class is templated over the types of the two input images and the
35021
type of the output image. Numeric conversions (castings) are done by
35024
Since the bitwise XOR operation is only defined in C++ for integer
35025
types, the images passed to this filter must comply with the
35026
requirement of using integer pixel type.
35028
The total operation over one pixel will be
35031
Where \"^\" is the boolean XOR operator in C++.
35037
Binary XOR (exclusive OR) two images
35039
itk::simple::Xor for the procedural interface
35041
itk::XorImageFilter for the Doxygen on the original ITK class.
35045
C++ includes: sitkXorImageFilter.h
35048
%feature("docstring") itk::simple::XorImageFilter::Execute "
35050
Execute the filter on the input images
35054
%feature("docstring") itk::simple::XorImageFilter::Execute "
35056
Execute the filter with an image and a constant
35060
%feature("docstring") itk::simple::XorImageFilter::Execute "
35063
%feature("docstring") itk::simple::XorImageFilter::GetName "
35069
%feature("docstring") itk::simple::XorImageFilter::ToString "
35071
Print ourselves out
35075
%feature("docstring") itk::simple::XorImageFilter::XorImageFilter "
35077
Default Constructor that takes no arguments and initializes default
35082
%feature("docstring") itk::simple::XorImageFilter::~XorImageFilter "
35089
%feature("docstring") itk::simple::YenThresholdImageFilter "
35091
Threshold an image using the Yen Threshold.
35094
This filter creates a binary thresholded image that separates an image
35095
into foreground and background components. The filter computes the
35096
threshold using the YenThresholdCalculator and applies that threshold to the input image using the BinaryThresholdImageFilter .
35100
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
35101
de Jouy-en-Josas, France.
35103
This implementation was taken from the Insight Journal paper: https://hdl.handle.net/10380/3279 or http://www.insight-journal.org/browse/publication/811
35107
HistogramThresholdImageFilter
35109
itk::simple::YenThreshold for the procedural interface
35111
itk::YenThresholdImageFilter for the Doxygen on the original ITK class.
35114
C++ includes: sitkYenThresholdImageFilter.h
35117
%feature("docstring") itk::simple::YenThresholdImageFilter::Execute "
35119
Execute the filter on the input image
35123
%feature("docstring") itk::simple::YenThresholdImageFilter::Execute "
35126
%feature("docstring") itk::simple::YenThresholdImageFilter::Execute "
35128
Execute the filter on the input image with the given parameters
35132
%feature("docstring") itk::simple::YenThresholdImageFilter::Execute "
35135
%feature("docstring") itk::simple::YenThresholdImageFilter::GetInsideValue "
35137
Get the \"inside\" pixel value.
35141
%feature("docstring") itk::simple::YenThresholdImageFilter::GetMaskOutput "
35144
%feature("docstring") itk::simple::YenThresholdImageFilter::GetMaskValue "
35147
%feature("docstring") itk::simple::YenThresholdImageFilter::GetName "
35153
%feature("docstring") itk::simple::YenThresholdImageFilter::GetNumberOfHistogramBins "
35156
%feature("docstring") itk::simple::YenThresholdImageFilter::GetOutsideValue "
35158
Get the \"outside\" pixel value.
35162
%feature("docstring") itk::simple::YenThresholdImageFilter::GetThreshold "
35164
Get the computed threshold.
35167
This is a measurement. Its value is updated in the Execute methods, so
35168
the value will only be valid after an execution.
35172
%feature("docstring") itk::simple::YenThresholdImageFilter::MaskOutputOff "
35175
%feature("docstring") itk::simple::YenThresholdImageFilter::MaskOutputOn "
35177
Set the value of MaskOutput to true or false respectfully.
35181
%feature("docstring") itk::simple::YenThresholdImageFilter::SetInsideValue "
35183
Set the \"inside\" pixel value.
35187
%feature("docstring") itk::simple::YenThresholdImageFilter::SetMaskOutput "
35189
Do you want the output to be masked by the mask used in histogram
35190
construction. Only relevant if masking is in use.
35194
%feature("docstring") itk::simple::YenThresholdImageFilter::SetMaskValue "
35196
The value in the mask image, if used, indicating voxels that should be
35197
included. Default is the max of pixel type, as in the
35198
MaskedImageToHistogramFilter
35202
%feature("docstring") itk::simple::YenThresholdImageFilter::SetNumberOfHistogramBins "
35204
Set/Get the number of histogram bins.
35208
%feature("docstring") itk::simple::YenThresholdImageFilter::SetOutsideValue "
35210
Set the \"outside\" pixel value. The default value NumericTraits<OutputPixelType>::Zero.
35214
%feature("docstring") itk::simple::YenThresholdImageFilter::ToString "
35216
Print ourselves out
35220
%feature("docstring") itk::simple::YenThresholdImageFilter::YenThresholdImageFilter "
35222
Default Constructor that takes no arguments and initializes default
35227
%feature("docstring") itk::simple::YenThresholdImageFilter::~YenThresholdImageFilter "
35234
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter "
35236
This filter implements a zero-crossing based edge detecor.
35239
The zero-crossing based edge detector looks for pixels in the
35240
Laplacian of an image where the value of the Laplacian passes through
35241
zero points where the Laplacian changes sign. Such points often occur
35242
at \"edges\" in images i.e. points where the intensity of the image
35243
changes rapidly, but they also occur at places that are not as easy to
35244
associate with edges. It is best to think of the zero crossing
35245
detector as some sort of feature detector rather than as a specific
35249
Zero crossings always lie on closed contours and so the output from
35250
the zero crossing detector is usually a binary image with single pixel
35251
thickness lines showing the positions of the zero crossing points.
35253
In this implementation, the input image is first smoothed with a
35254
Gaussian filter, then the LaplacianImageFilter is applied to smoothed image. Finally the zero-crossing of the
35255
Laplacian of the smoothed image is detected. The output is a binary
35258
The input to the filter should be a scalar, itk::Image of arbitrary dimension. The output image is a binary, labeled image.
35259
See itkZeroCrossingImageFilter for more information on requirements of
35260
the data type of the output.
35262
To use this filter, first set the parameters (variance and maximum
35263
error) needed by the embedded DiscreteGaussianImageFilter , i.e. See DiscreteGaussianImageFilter for information about these parameters. Optionally, you may also set
35264
foreground and background values for the zero-crossing filter. The
35265
default label values are Zero for the background and One for the
35266
foreground, as defined in NumericTraits for the data type of the output image.
35269
DiscreteGaussianImageFilter
35271
LaplacianImageFilter
35273
ZeroCrossingImageFilter
35275
itk::simple::ZeroCrossingBasedEdgeDetection for the procedural interface
35277
itk::ZeroCrossingBasedEdgeDetectionImageFilter for the Doxygen on the original ITK class.
35280
C++ includes: sitkZeroCrossingBasedEdgeDetectionImageFilter.h
35283
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::Execute "
35285
Execute the filter on the input image
35289
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::Execute "
35291
Execute the filter on the input image with the given parameters
35295
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::GetBackgroundValue "
35297
Get/Set the label values for the ZeroCrossingImageFilter
35301
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::GetForegroundValue "
35303
Get/Set the label values for the ZeroCrossingImageFilter
35307
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::GetMaximumError "
35309
Standard get/set macros for Gaussian filter parameters.
35313
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::GetName "
35319
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::GetVariance "
35321
Standard get/set macros for Gaussian filter parameters.
35325
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::SetBackgroundValue "
35327
Get/Set the label values for the ZeroCrossingImageFilter
35331
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::SetForegroundValue "
35333
Get/Set the label values for the ZeroCrossingImageFilter
35337
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::SetMaximumError "
35339
Set the MaximumError parameter needed by the embedded gaussian filter
35340
This value is used to set the desired maximum error of the gaussian
35341
approximation. Maximum error is the difference between the area under
35342
the discrete Gaussian curve and the area under the continuous
35343
Gaussian. Maximum error affects the Gaussian operator size. The value
35344
must be between 0.0 and 1.0.
35348
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::SetVariance "
35350
Set the variance parameter needed by the embedded gaussian filter
35354
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::ToString "
35356
Print ourselves out
35360
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::ZeroCrossingBasedEdgeDetectionImageFilter "
35362
Default Constructor that takes no arguments and initializes default
35367
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter::~ZeroCrossingBasedEdgeDetectionImageFilter "
35374
%feature("docstring") itk::simple::ZeroCrossingImageFilter "
35376
This filter finds the closest pixel to the zero-crossings (sign
35377
changes) in a signed itk::Image .
35380
Pixels closest to zero-crossings are labeled with a foreground value.
35381
All other pixels are marked with a background value. The algorithm
35382
works by detecting differences in sign among neighbors using city-
35383
block style connectivity (4-neighbors in 2d, 6-neighbors in 3d, etc.).
35386
The input to this filter is an itk::Image of arbitrary dimension. The algorithm assumes a signed data type
35387
(zero-crossings are not defined for unsigned data types), and requires
35388
that operator>, operator<, operator==, and operator!= are defined.
35390
The output of the filter is a binary, labeled image of user-specified
35391
type. By default, zero-crossing pixels are labeled with a default
35392
\"foreground\" value of itk::NumericTraits<OutputDataType>::OneValue() , where OutputDataType is the data type of the output image. All
35393
other pixels are labeled with a default \"background\" value of itk::NumericTraits<OutputDataType>::ZeroValue() .
35395
There are two parameters for this filter. ForegroundValue is the value
35396
that marks zero-crossing pixels. The BackgroundValue is the value
35397
given to all other pixels.
35404
NeighborhoodOperator
35406
NeighborhoodIterator
35411
Find zero crossings in a signed image
35413
itk::simple::ZeroCrossing for the procedural interface
35415
itk::ZeroCrossingImageFilter for the Doxygen on the original ITK class.
35419
C++ includes: sitkZeroCrossingImageFilter.h
35422
%feature("docstring") itk::simple::ZeroCrossingImageFilter::Execute "
35424
Execute the filter on the input image
35428
%feature("docstring") itk::simple::ZeroCrossingImageFilter::Execute "
35430
Execute the filter on the input image with the given parameters
35434
%feature("docstring") itk::simple::ZeroCrossingImageFilter::GetBackgroundValue "
35436
Set/Get the label value for non-zero-crossing pixels.
35440
%feature("docstring") itk::simple::ZeroCrossingImageFilter::GetForegroundValue "
35442
Set/Get the label value for zero-crossing pixels.
35446
%feature("docstring") itk::simple::ZeroCrossingImageFilter::GetName "
35452
%feature("docstring") itk::simple::ZeroCrossingImageFilter::SetBackgroundValue "
35454
Set/Get the label value for non-zero-crossing pixels.
35458
%feature("docstring") itk::simple::ZeroCrossingImageFilter::SetForegroundValue "
35460
Set/Get the label value for zero-crossing pixels.
35464
%feature("docstring") itk::simple::ZeroCrossingImageFilter::ToString "
35466
Print ourselves out
35470
%feature("docstring") itk::simple::ZeroCrossingImageFilter::ZeroCrossingImageFilter "
35472
Default Constructor that takes no arguments and initializes default
35477
%feature("docstring") itk::simple::ZeroCrossingImageFilter::~ZeroCrossingImageFilter "
35484
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter "
35486
Increase the image size by padding according to the zero-flux Neumann
35487
boundary condition.
35490
A filter which extends the image size and fill the missing pixels
35491
according to a Neumann boundary condition where first, upwind
35492
derivatives on the boundary are zero. This is a useful condition in
35493
solving some classes of differential equations.
35495
For example, invoking this filter on an image with a corner like: returns the following padded image:
35498
Gaetan Lehmann. Biologie du Developpement et de la Reproduction, INRA
35499
de Jouy-en-Josas, France.
35502
WrapPadImageFilter , MirrorPadImageFilter , ConstantPadImageFilter , ZeroFluxNeumannBoundaryCondition
35504
itk::simple::ZeroFluxNeumannPad for the procedural interface
35506
itk::ZeroFluxNeumannPadImageFilter for the Doxygen on the original ITK class.
35509
C++ includes: sitkZeroFluxNeumannPadImageFilter.h
35512
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::Execute "
35514
Execute the filter on the input image
35518
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::Execute "
35520
Execute the filter on the input image with the given parameters
35524
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::GetName "
35530
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::GetPadLowerBound "
35533
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::GetPadUpperBound "
35536
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::SetPadLowerBound "
35539
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::SetPadUpperBound "
35542
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::ToString "
35544
Print ourselves out
35548
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::ZeroFluxNeumannPadImageFilter "
35550
Default Constructor that takes no arguments and initializes default
35555
%feature("docstring") itk::simple::ZeroFluxNeumannPadImageFilter::~ZeroFluxNeumannPadImageFilter "
35562
%feature("docstring") itk::simple::DualMemberFunctionFactory "
35564
A class used to instantiate and generate function objects of templated
35565
member functions with two template arguments.
35572
TMemberFunctionPointer:
35573
is the type of pointer to member function
35575
Example member function and pointer:
35577
The provided Addressor will instantiate the templeted member functions
35578
by taking the address in the RegisterMethods. Later they can be
35579
retrieve with the GetMemberFunction method, which returns a function
35580
object with the same arguments as the templated member function
35583
An instance of a MemberFunctionFactory is bound to a specific instance of an object, so that the returned
35584
function object does not need to have the calling object specified.
35588
Use this class with caution because it can instantiate a combinatorial
35592
MemberFunctionFactory
35595
C++ includes: sitkDualMemberFunctionFactory.h
35598
%feature("docstring") itk::simple::DualMemberFunctionFactory::DualMemberFunctionFactory "
35600
Constructor which permanently binds the constructed object to pObject.
35604
%feature("docstring") itk::simple::DualMemberFunctionFactory::GetMemberFunction "
35606
Returns a function object for the combination of PixelID1 and
35607
PixelID2, and image dimension.
35610
pixelID1 or pixelID2 is the value of Image::GetPixelIDValue(), or PixelIDToPixelIDValue<PixelIDType>::Result
35612
imageDimension is the the value returned by Image::GetDimension()
35616
If the requested member function is not registered then an exception
35617
is generated. The returned function object is guaranteed to be valid.
35621
%feature("docstring") itk::simple::DualMemberFunctionFactory::HasMemberFunction "
35623
Query to determine if an member function has been registered for
35624
pixelID1, pixelID2 and imageDimension.
35628
%feature("docstring") itk::simple::DualMemberFunctionFactory::Register "
35630
Registers a specific member function.
35633
Registers a member function templated over TImageType1 and TImageType2
35638
%feature("docstring") itk::simple::MemberFunctionFactory "
35640
A class used to instantiate and generate function object to templated
35648
TMemberFunctionPointer:
35649
is the type of pointer to member function
35651
Example member function pointer:
35653
The RegisterMemberFunctions instantiate the templeted member functions
35654
and registers the member function pointer, so that it be used for
35655
dispatch later. Later they can be retrieve with the GetMemberFunction
35656
methods, which return a function object with the same arguments as the
35657
templated member function pointer.
35659
An instance of a MemberFunctionFactory is bound to a specific instance of an object, so that the returned
35660
function object does not need to have the calling object specified.
35662
C++ includes: sitkMemberFunctionFactory.h
35665
%feature("docstring") itk::simple::MemberFunctionFactory::GetMemberFunction "
35667
Returns a function object for the PixelIndex, and image dimension.
35670
pixelID is the value of Image::GetPixelIDValue(), or PixelIDToPixelIDValue<PixelIDType>::Result
35672
imageDimension is the the value returned by Image::GetDimension()
35676
If the requested member function is not registered then an exception
35677
is generated. The returned function object is guaranteed to be valid.
35681
%feature("docstring") itk::simple::MemberFunctionFactory::HasMemberFunction "
35683
Query to determine if an member function has been registered for
35684
pixelID and imageDimension.
35688
%feature("docstring") itk::simple::MemberFunctionFactory::MemberFunctionFactory "
35690
Constructor which permanently binds the constructed object to pObject.
35694
%feature("docstring") itk::simple::MemberFunctionFactory::Register "
35696
Registers a specific member function.
35699
Registers a member function which will be dispatched to the TImageType
35705
%feature("docstring") itk::simple::MemberFunctionFactoryBase "
35707
A base class for the MemberFunctionFactory.
35710
This class is for specialization needed for different arity for the
35711
templated member function pointer
35713
C++ includes: sitkMemberFunctionFactoryBase.h
35717
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 0 > "
35718
C++ includes: sitkMemberFunctionFactoryBase.h
35722
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 1 > "
35723
C++ includes: sitkMemberFunctionFactoryBase.h
35727
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 2 > "
35728
C++ includes: sitkMemberFunctionFactoryBase.h
35732
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 3 > "
35733
C++ includes: sitkMemberFunctionFactoryBase.h
35737
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 4 > "
35738
C++ includes: sitkMemberFunctionFactoryBase.h
35742
%feature("docstring") itk::simple::MemberFunctionFactoryBase< TMemberFunctionPointer, TKey, 5 > "
35743
C++ includes: sitkMemberFunctionFactoryBase.h
35746
%feature("docstring") itk::simple::Abs "
35748
Computes the absolute value of each pixel.
35751
This function directly calls the execute method of AbsImageFilter in order to support a procedural API
35755
itk::simple::AbsImageFilter for the object oriented interface
35760
%feature("docstring") itk::simple::AbsoluteValueDifference "
35762
Implements pixel-wise the computation of absolute value difference.
35765
This function directly calls the execute method of AbsoluteValueDifferenceImageFilter in order to support a procedural API
35769
itk::simple::AbsoluteValueDifferenceImageFilter for the object oriented interface
35774
%feature("docstring") itk::simple::AbsoluteValueDifference "
35777
%feature("docstring") itk::simple::AbsoluteValueDifference "
35780
%feature("docstring") itk::simple::Acos "
35782
Computes the inverse cosine of each pixel.
35785
This function directly calls the execute method of AcosImageFilter in order to support a procedural API
35789
itk::simple::AcosImageFilter for the object oriented interface
35794
%feature("docstring") itk::simple::AdaptiveHistogramEqualization "
35796
Power Law Adaptive Histogram Equalization.
35799
This function directly calls the execute method of AdaptiveHistogramEqualizationImageFilter in order to support a procedural API
35803
itk::simple::AdaptiveHistogramEqualizationImageFilter for the object oriented interface
35808
%feature("docstring") itk::simple::Add "
35810
Pixel-wise addition of two images.
35813
This function directly calls the execute method of AddImageFilter in order to support a procedural API
35817
itk::simple::AddImageFilter for the object oriented interface
35822
%feature("docstring") itk::simple::Add "
35825
%feature("docstring") itk::simple::Add "
35828
%feature("docstring") itk::simple::AdditiveGaussianNoise "
35830
Alter an image with additive Gaussian white noise.
35833
This function directly calls the execute method of AdditiveGaussianNoiseImageFilter in order to support a procedural API
35837
itk::simple::AdditiveGaussianNoiseImageFilter for the object oriented interface
35842
%feature("docstring") itk::simple::AggregateLabelMap "
35844
Collapses all labels into the first label.
35847
This function directly calls the execute method of AggregateLabelMapFilter in order to support a procedural API
35851
itk::simple::AggregateLabelMapFilter for the object oriented interface
35856
%feature("docstring") itk::simple::And "
35858
Implements the AND bitwise operator pixel-wise between two images.
35861
This function directly calls the execute method of AndImageFilter in order to support a procedural API
35865
itk::simple::AndImageFilter for the object oriented interface
35870
%feature("docstring") itk::simple::And "
35873
%feature("docstring") itk::simple::And "
35876
%feature("docstring") itk::simple::AntiAliasBinary "
35878
A method for estimation of a surface from a binary volume.
35881
This function directly calls the execute method of AntiAliasBinaryImageFilter in order to support a procedural API
35885
itk::simple::AntiAliasBinaryImageFilter for the object oriented interface
35890
%feature("docstring") itk::simple::ApproximateSignedDistanceMap "
35892
Create a map of the approximate signed distance from the boundaries of
35896
This function directly calls the execute method of ApproximateSignedDistanceMapImageFilter in order to support a procedural API
35900
itk::simple::ApproximateSignedDistanceMapImageFilter for the object oriented interface
35905
%feature("docstring") itk::simple::Asin "
35907
Computes the sine of each pixel.
35910
This function directly calls the execute method of AsinImageFilter in order to support a procedural API
35914
itk::simple::AsinImageFilter for the object oriented interface
35919
%feature("docstring") itk::simple::Atan "
35921
Computes the one-argument inverse tangent of each pixel.
35924
This function directly calls the execute method of AtanImageFilter in order to support a procedural API
35928
itk::simple::AtanImageFilter for the object oriented interface
35933
%feature("docstring") itk::simple::Atan2 "
35935
Computes two argument inverse tangent.
35938
This function directly calls the execute method of Atan2ImageFilter in order to support a procedural API
35942
itk::simple::Atan2ImageFilter for the object oriented interface
35947
%feature("docstring") itk::simple::Atan2 "
35950
%feature("docstring") itk::simple::Atan2 "
35953
%feature("docstring") itk::simple::Bilateral "
35955
Blurs an image while preserving edges.
35958
This function directly calls the execute method of BilateralImageFilter in order to support a procedural API
35962
itk::simple::BilateralImageFilter for the object oriented interface
35967
%feature("docstring") itk::simple::BinaryClosingByReconstruction "
35969
itk::simple::BinaryClosingByReconstructionImageFilter Functional Interface
35971
This function directly calls the execute method of BinaryClosingByReconstructionImageFilter in order to support a fully functional API
35975
%feature("docstring") itk::simple::BinaryClosingByReconstruction "
35977
itk::simple::BinaryClosingByReconstructionImageFilter Functional Interface
35979
This function directly calls the execute method of BinaryClosingByReconstructionImageFilter in order to support a fully functional API
35983
%feature("docstring") itk::simple::BinaryContour "
35985
Labels the pixels on the border of the objects in a binary image.
35988
This function directly calls the execute method of BinaryContourImageFilter in order to support a procedural API
35992
itk::simple::BinaryContourImageFilter for the object oriented interface
35997
%feature("docstring") itk::simple::BinaryDilate "
35999
itk::simple::BinaryDilateImageFilter Functional Interface
36001
This function directly calls the execute method of BinaryDilateImageFilter in order to support a fully functional API
36005
%feature("docstring") itk::simple::BinaryDilate "
36007
itk::simple::BinaryDilateImageFilter Functional Interface
36009
This function directly calls the execute method of BinaryDilateImageFilter in order to support a fully functional API
36013
%feature("docstring") itk::simple::BinaryErode "
36015
itk::simple::BinaryErodeImageFilter Functional Interface
36017
This function directly calls the execute method of BinaryErodeImageFilter in order to support a fully functional API
36021
%feature("docstring") itk::simple::BinaryErode "
36023
itk::simple::BinaryErodeImageFilter Functional Interface
36025
This function directly calls the execute method of BinaryErodeImageFilter in order to support a fully functional API
36029
%feature("docstring") itk::simple::BinaryFillhole "
36031
Remove holes not connected to the boundary of the image.
36034
This function directly calls the execute method of BinaryFillholeImageFilter in order to support a procedural API
36038
itk::simple::BinaryFillholeImageFilter for the object oriented interface
36043
%feature("docstring") itk::simple::BinaryGrindPeak "
36045
Remove the objects not connected to the boundary of the image.
36048
This function directly calls the execute method of BinaryGrindPeakImageFilter in order to support a procedural API
36052
itk::simple::BinaryGrindPeakImageFilter for the object oriented interface
36057
%feature("docstring") itk::simple::BinaryImageToLabelMap "
36059
Label the connected components in a binary image and produce a
36060
collection of label objects.
36063
This function directly calls the execute method of BinaryImageToLabelMapFilter in order to support a procedural API
36067
itk::simple::BinaryImageToLabelMapFilter for the object oriented interface
36072
%feature("docstring") itk::simple::BinaryMagnitude "
36074
Computes the square root of the sum of squares of corresponding input
36078
This function directly calls the execute method of BinaryMagnitudeImageFilter in order to support a procedural API
36082
itk::simple::BinaryMagnitudeImageFilter for the object oriented interface
36087
%feature("docstring") itk::simple::BinaryMedian "
36089
Applies a version of the median filter optimized for binary images.
36092
This function directly calls the execute method of BinaryMedianImageFilter in order to support a procedural API
36096
itk::simple::BinaryMedianImageFilter for the object oriented interface
36101
%feature("docstring") itk::simple::BinaryMinMaxCurvatureFlow "
36103
Denoise a binary image using min/max curvature flow.
36106
This function directly calls the execute method of BinaryMinMaxCurvatureFlowImageFilter in order to support a procedural API
36110
itk::simple::BinaryMinMaxCurvatureFlowImageFilter for the object oriented interface
36115
%feature("docstring") itk::simple::BinaryMorphologicalClosing "
36117
itk::simple::BinaryMorphologicalClosingImageFilter Functional Interface
36119
This function directly calls the execute method of BinaryMorphologicalClosingImageFilter in order to support a fully functional API
36123
%feature("docstring") itk::simple::BinaryMorphologicalClosing "
36125
itk::simple::BinaryMorphologicalClosingImageFilter Functional Interface
36127
This function directly calls the execute method of BinaryMorphologicalClosingImageFilter in order to support a fully functional API
36131
%feature("docstring") itk::simple::BinaryMorphologicalOpening "
36133
itk::simple::BinaryMorphologicalOpeningImageFilter Functional Interface
36135
This function directly calls the execute method of BinaryMorphologicalOpeningImageFilter in order to support a fully functional API
36139
%feature("docstring") itk::simple::BinaryMorphologicalOpening "
36141
itk::simple::BinaryMorphologicalOpeningImageFilter Functional Interface
36143
This function directly calls the execute method of BinaryMorphologicalOpeningImageFilter in order to support a fully functional API
36147
%feature("docstring") itk::simple::BinaryNot "
36149
Implements the BinaryNot logical operator pixel-wise between two
36153
This function directly calls the execute method of BinaryNotImageFilter in order to support a procedural API
36157
itk::simple::BinaryNotImageFilter for the object oriented interface
36162
%feature("docstring") itk::simple::BinaryOpeningByReconstruction "
36164
itk::simple::BinaryOpeningByReconstructionImageFilter Functional Interface
36166
This function directly calls the execute method of BinaryOpeningByReconstructionImageFilter in order to support a fully functional API
36170
%feature("docstring") itk::simple::BinaryOpeningByReconstruction "
36172
itk::simple::BinaryOpeningByReconstructionImageFilter Functional Interface
36174
This function directly calls the execute method of BinaryOpeningByReconstructionImageFilter in order to support a fully functional API
36178
%feature("docstring") itk::simple::BinaryProjection "
36183
This function directly calls the execute method of BinaryProjectionImageFilter in order to support a procedural API
36187
itk::simple::BinaryProjectionImageFilter for the object oriented interface
36192
%feature("docstring") itk::simple::BinaryReconstructionByDilation "
36194
binary reconstruction by dilation of an image
36197
This function directly calls the execute method of BinaryReconstructionByDilationImageFilter in order to support a procedural API
36201
itk::simple::BinaryReconstructionByDilationImageFilter for the object oriented interface
36206
%feature("docstring") itk::simple::BinaryReconstructionByErosion "
36208
binary reconstruction by erosion of an image
36211
This function directly calls the execute method of BinaryReconstructionByErosionImageFilter in order to support a procedural API
36215
itk::simple::BinaryReconstructionByErosionImageFilter for the object oriented interface
36220
%feature("docstring") itk::simple::BinaryThinning "
36222
This filter computes one-pixel-wide edges of the input image.
36225
This function directly calls the execute method of BinaryThinningImageFilter in order to support a procedural API
36229
itk::simple::BinaryThinningImageFilter for the object oriented interface
36234
%feature("docstring") itk::simple::BinaryThreshold "
36236
Binarize an input image by thresholding.
36239
This function directly calls the execute method of BinaryThresholdImageFilter in order to support a procedural API
36243
itk::simple::BinaryThresholdImageFilter for the object oriented interface
36248
%feature("docstring") itk::simple::BinaryThresholdProjection "
36250
BinaryThreshold projection.
36253
This function directly calls the execute method of BinaryThresholdProjectionImageFilter in order to support a procedural API
36257
itk::simple::BinaryThresholdProjectionImageFilter for the object oriented interface
36262
%feature("docstring") itk::simple::BinomialBlur "
36264
Performs a separable blur on each dimension of an image.
36267
This function directly calls the execute method of BinomialBlurImageFilter in order to support a procedural API
36271
itk::simple::BinomialBlurImageFilter for the object oriented interface
36276
%feature("docstring") itk::simple::BinShrink "
36278
Reduce the size of an image by an integer factor in each dimension
36279
while performing averaging of an input neighborhood.
36282
This function directly calls the execute method of BinShrinkImageFilter in order to support a procedural API
36286
itk::simple::BinShrinkImageFilter for the object oriented interface
36291
%feature("docstring") itk::simple::BitwiseNot "
36293
Implements pixel-wise generic operation on one image.
36296
This function directly calls the execute method of BitwiseNotImageFilter in order to support a procedural API
36300
itk::simple::BitwiseNotImageFilter for the object oriented interface
36305
%feature("docstring") itk::simple::BlackTopHat "
36307
itk::simple::BlackTopHatImageFilter Functional Interface
36309
This function directly calls the execute method of BlackTopHatImageFilter in order to support a fully functional API
36313
%feature("docstring") itk::simple::BlackTopHat "
36315
itk::simple::BlackTopHatImageFilter Functional Interface
36317
This function directly calls the execute method of BlackTopHatImageFilter in order to support a fully functional API
36321
%feature("docstring") itk::simple::BoundedReciprocal "
36323
Computes 1/(1+x) for each pixel in the image.
36326
This function directly calls the execute method of BoundedReciprocalImageFilter in order to support a procedural API
36330
itk::simple::BoundedReciprocalImageFilter for the object oriented interface
36335
%feature("docstring") itk::simple::BoxMean "
36337
Implements a fast rectangular mean filter using the accumulator
36341
This function directly calls the execute method of BoxMeanImageFilter in order to support a procedural API
36345
itk::simple::BoxMeanImageFilter for the object oriented interface
36350
%feature("docstring") itk::simple::BoxSigma "
36352
Implements a fast rectangular sigma filter using the accumulator
36356
This function directly calls the execute method of BoxSigmaImageFilter in order to support a procedural API
36360
itk::simple::BoxSigmaImageFilter for the object oriented interface
36365
%feature("docstring") itk::simple::BSplineTransformInitializer "
36367
BSplineTransformInitializerFilter is a helper class intended to initialize the control point grid such
36368
that it has a physically consistent definition. It sets the transform
36369
domain origin, physical dimensions and direction from information
36370
obtained from the image. It also sets the mesh size if asked to do so
36371
by calling SetTransformDomainMeshSize()before calling
36372
InitializeTransform().
36375
This function directly calls the execute method of BSplineTransformInitializerFilter in order to support a procedural API
36379
itk::simple::BSplineTransformInitializerFilter for the object oriented interface
36384
%feature("docstring") itk::simple::CannyEdgeDetection "
36386
This filter is an implementation of a Canny edge detector for scalar-
36390
This function directly calls the execute method of CannyEdgeDetectionImageFilter in order to support a procedural API
36394
itk::simple::CannyEdgeDetectionImageFilter for the object oriented interface
36399
%feature("docstring") itk::simple::Cast "
36402
%feature("docstring") itk::simple::CenteredTransformInitializer "
36404
CenteredTransformInitializer is a helper class intended to initialize the center of rotation and
36405
the translation of Transforms having the center of rotation among
36409
This function directly calls the execute method of CenteredTransformInitializerFilter in order to support a procedural API
36413
itk::simple::CenteredTransformInitializerFilter for the object oriented interface
36418
%feature("docstring") itk::simple::CenteredVersorTransformInitializer "
36420
CenteredVersorTransformInitializer is a helper class intended to initialize the center of rotation,
36421
versor, and translation of the VersorRigid3DTransform.
36424
This function directly calls the execute method of
36425
CenteredVectorTransformInitializerFilter in order to support a
36430
itk::simple::CenteredVersorTransformInitializerFilter for the object oriented interface
36435
%feature("docstring") itk::simple::ChangeLabel "
36437
Change Sets of Labels.
36440
This function directly calls the execute method of ChangeLabelImageFilter in order to support a procedural API
36444
itk::simple::ChangeLabelImageFilter for the object oriented interface
36449
%feature("docstring") itk::simple::ChangeLabelLabelMap "
36451
Replace the label Ids of selected LabelObjects with new label Ids.
36454
This function directly calls the execute method of ChangeLabelLabelMapFilter in order to support a procedural API
36458
itk::simple::ChangeLabelLabelMapFilter for the object oriented interface
36463
%feature("docstring") itk::simple::CheckerBoard "
36465
Combines two images in a checkerboard pattern.
36468
This function directly calls the execute method of CheckerBoardImageFilter in order to support a procedural API
36472
itk::simple::CheckerBoardImageFilter for the object oriented interface
36477
%feature("docstring") itk::simple::Clamp "
36479
Casts input pixels to output pixel type and clamps the output pixel
36480
values to a specified range.
36483
This function directly calls the execute method of ClampImageFilter in order to support a procedural API
36487
itk::simple::ClampImageFilter for the object oriented interface
36492
%feature("docstring") itk::simple::ClosingByReconstruction "
36494
itk::simple::ClosingByReconstructionImageFilter Functional Interface
36496
This function directly calls the execute method of ClosingByReconstructionImageFilter in order to support a fully functional API
36500
%feature("docstring") itk::simple::ClosingByReconstruction "
36502
itk::simple::ClosingByReconstructionImageFilter Functional Interface
36504
This function directly calls the execute method of ClosingByReconstructionImageFilter in order to support a fully functional API
36508
%feature("docstring") itk::simple::CollidingFronts "
36510
Selects a region of space where two independent fronts run towards
36514
This function directly calls the execute method of CollidingFrontsImageFilter in order to support a procedural API
36518
itk::simple::CollidingFrontsImageFilter for the object oriented interface
36523
%feature("docstring") itk::simple::ComplexToImaginary "
36525
Computes pixel-wise the imaginary part of a complex image.
36528
This function directly calls the execute method of ComplexToImaginaryImageFilter in order to support a procedural API
36532
itk::simple::ComplexToImaginaryImageFilter for the object oriented interface
36537
%feature("docstring") itk::simple::ComplexToModulus "
36539
Computes pixel-wise the Modulus of a complex image.
36542
This function directly calls the execute method of ComplexToModulusImageFilter in order to support a procedural API
36546
itk::simple::ComplexToModulusImageFilter for the object oriented interface
36551
%feature("docstring") itk::simple::ComplexToPhase "
36553
Computes pixel-wise the modulus of a complex image.
36556
This function directly calls the execute method of ComplexToPhaseImageFilter in order to support a procedural API
36560
itk::simple::ComplexToPhaseImageFilter for the object oriented interface
36565
%feature("docstring") itk::simple::ComplexToReal "
36567
Computes pixel-wise the real(x) part of a complex image.
36570
This function directly calls the execute method of ComplexToRealImageFilter in order to support a procedural API
36574
itk::simple::ComplexToRealImageFilter for the object oriented interface
36579
%feature("docstring") itk::simple::ConfidenceConnected "
36581
itk::simple::ConfidenceConnectedImageFilter Functional Interface
36583
This function directly calls the execute method of ConfidenceConnectedImageFilter in order to support a fully functional API
36587
%feature("docstring") itk::simple::ConnectedComponent "
36589
Label the objects in a binary image.
36592
This function directly calls the execute method of ConnectedComponentImageFilter in order to support a procedural API
36596
itk::simple::ConnectedComponentImageFilter for the object oriented interface
36601
%feature("docstring") itk::simple::ConnectedThreshold "
36603
itk::simple::ConnectedThresholdImageFilter Functional Interface
36605
This function directly calls the execute method of ConnectedThresholdImageFilter in order to support a fully functional API
36609
%feature("docstring") itk::simple::ConstantPad "
36611
Increase the image size by padding with a constant value.
36614
This function directly calls the execute method of ConstantPadImageFilter in order to support a procedural API
36618
itk::simple::ConstantPadImageFilter for the object oriented interface
36623
%feature("docstring") itk::simple::Convolution "
36625
Convolve a given image with an arbitrary image kernel.
36628
This function directly calls the execute method of ConvolutionImageFilter in order to support a procedural API
36632
itk::simple::ConvolutionImageFilter for the object oriented interface
36637
%feature("docstring") itk::simple::Cos "
36639
Computes the cosine of each pixel.
36642
This function directly calls the execute method of CosImageFilter in order to support a procedural API
36646
itk::simple::CosImageFilter for the object oriented interface
36651
%feature("docstring") itk::simple::CreateKernel "
36654
%feature("docstring") itk::simple::Crop "
36656
Decrease the image size by cropping the image by an itk::Size at both the upper and lower bounds of the largest possible region.
36659
This function directly calls the execute method of CropImageFilter in order to support a procedural API
36663
itk::simple::CropImageFilter for the object oriented interface
36668
%feature("docstring") itk::simple::CurvatureAnisotropicDiffusion "
36670
itk::simple::CurvatureAnisotropicDiffusionImageFilter Procedural Interface
36673
This function directly calls the execute method of CurvatureAnisotropicDiffusionImageFilter in order to support a procedural API
36677
itk::simple::CurvatureAnisotropicDiffusionImageFilter for the object oriented interface
36682
%feature("docstring") itk::simple::CurvatureFlow "
36684
Denoise an image using curvature driven flow.
36687
This function directly calls the execute method of CurvatureFlowImageFilter in order to support a procedural API
36691
itk::simple::CurvatureFlowImageFilter for the object oriented interface
36696
%feature("docstring") itk::simple::CyclicShift "
36698
Perform a cyclic spatial shift of image intensities on the image grid.
36701
This function directly calls the execute method of CyclicShiftImageFilter in order to support a procedural API
36705
itk::simple::CyclicShiftImageFilter for the object oriented interface
36710
%feature("docstring") itk::simple::DanielssonDistanceMap "
36712
This filter computes the distance map of the input image as an
36713
approximation with pixel accuracy to the Euclidean distance.
36716
This function directly calls the execute method of DanielssonDistanceMapImageFilter in order to support a procedural API
36720
itk::simple::DanielssonDistanceMapImageFilter for the object oriented interface
36725
%feature("docstring") itk::simple::Derivative "
36727
Computes the directional derivative of an image. The directional
36728
derivative at each pixel location is computed by convolution with a
36729
derivative operator of user-specified order.
36732
This function directly calls the execute method of DerivativeImageFilter in order to support a procedural API
36736
itk::simple::DerivativeImageFilter for the object oriented interface
36741
%feature("docstring") itk::simple::DilateObjectMorphology "
36743
itk::simple::DilateObjectMorphologyImageFilter Functional Interface
36745
This function directly calls the execute method of DilateObjectMorphologyImageFilter in order to support a fully functional API
36749
%feature("docstring") itk::simple::DilateObjectMorphology "
36751
itk::simple::DilateObjectMorphologyImageFilter Functional Interface
36753
This function directly calls the execute method of DilateObjectMorphologyImageFilter in order to support a fully functional API
36757
%feature("docstring") itk::simple::DiscreteGaussian "
36759
Blurs an image by separable convolution with discrete gaussian
36760
kernels. This filter performs Gaussian blurring by separable
36761
convolution of an image and a discrete Gaussian operator (kernel).
36764
This function directly calls the execute method of DiscreteGaussianImageFilter in order to support a procedural API
36768
itk::simple::DiscreteGaussianImageFilter for the object oriented interface
36773
%feature("docstring") itk::simple::DiscreteGaussianDerivative "
36775
Calculates image derivatives using discrete derivative gaussian
36776
kernels. This filter calculates Gaussian derivative by separable
36777
convolution of an image and a discrete Gaussian derivative operator
36781
This function directly calls the execute method of DiscreteGaussianDerivativeImageFilter in order to support a procedural API
36785
itk::simple::DiscreteGaussianDerivativeImageFilter for the object oriented interface
36790
%feature("docstring") itk::simple::DisplacementFieldJacobianDeterminant "
36792
Computes a scalar image from a vector image (e.g., deformation field)
36793
input, where each output scalar at each pixel is the Jacobian
36794
determinant of the vector field at that location. This calculation is
36795
correct in the case where the vector image is a \"displacement\" from
36796
the current location. The computation for the jacobian determinant is:
36797
det[ dT/dx ] = det[ I + du/dx ].
36800
This function directly calls the execute method of DisplacementFieldJacobianDeterminantFilter in order to support a procedural API
36804
itk::simple::DisplacementFieldJacobianDeterminantFilter for the object oriented interface
36809
%feature("docstring") itk::simple::Divide "
36811
Pixel-wise division of two images.
36814
This function directly calls the execute method of DivideImageFilter in order to support a procedural API
36818
itk::simple::DivideImageFilter for the object oriented interface
36823
%feature("docstring") itk::simple::Divide "
36826
%feature("docstring") itk::simple::Divide "
36829
%feature("docstring") itk::simple::DivideFloor "
36831
Implements pixel-wise generic operation of two images, or of an image
36835
This function directly calls the execute method of DivideFloorImageFilter in order to support a procedural API
36839
itk::simple::DivideFloorImageFilter for the object oriented interface
36844
%feature("docstring") itk::simple::DivideFloor "
36847
%feature("docstring") itk::simple::DivideFloor "
36850
%feature("docstring") itk::simple::DivideReal "
36852
Implements pixel-wise generic operation of two images, or of an image
36856
This function directly calls the execute method of DivideRealImageFilter in order to support a procedural API
36860
itk::simple::DivideRealImageFilter for the object oriented interface
36865
%feature("docstring") itk::simple::DivideReal "
36868
%feature("docstring") itk::simple::DivideReal "
36871
%feature("docstring") itk::simple::DoubleThreshold "
36873
Binarize an input image using double thresholding.
36876
This function directly calls the execute method of DoubleThresholdImageFilter in order to support a procedural API
36880
itk::simple::DoubleThresholdImageFilter for the object oriented interface
36885
%feature("docstring") itk::simple::EdgePotential "
36887
Computes the edge potential of an image from the image gradient.
36890
This function directly calls the execute method of EdgePotentialImageFilter in order to support a procedural API
36894
itk::simple::EdgePotentialImageFilter for the object oriented interface
36899
%feature("docstring") itk::simple::Equal "
36901
Implements pixel-wise generic operation of two images, or of an image
36905
This function directly calls the execute method of EqualImageFilter in order to support a procedural API
36909
itk::simple::EqualImageFilter for the object oriented interface
36914
%feature("docstring") itk::simple::Equal "
36917
%feature("docstring") itk::simple::Equal "
36920
%feature("docstring") itk::simple::ErodeObjectMorphology "
36922
itk::simple::ErodeObjectMorphologyImageFilter Functional Interface
36924
This function directly calls the execute method of ErodeObjectMorphologyImageFilter in order to support a fully functional API
36928
%feature("docstring") itk::simple::ErodeObjectMorphology "
36930
itk::simple::ErodeObjectMorphologyImageFilter Functional Interface
36932
This function directly calls the execute method of ErodeObjectMorphologyImageFilter in order to support a fully functional API
36936
%feature("docstring") itk::simple::Exp "
36938
Computes the exponential function of each pixel.
36941
This function directly calls the execute method of ExpImageFilter in order to support a procedural API
36945
itk::simple::ExpImageFilter for the object oriented interface
36950
%feature("docstring") itk::simple::Expand "
36952
Expand the size of an image by an integer factor in each dimension.
36955
This function directly calls the execute method of ExpandImageFilter in order to support a procedural API
36959
itk::simple::ExpandImageFilter for the object oriented interface
36964
%feature("docstring") itk::simple::ExpNegative "
36966
Computes the function exp(-K.x) for each input pixel.
36969
This function directly calls the execute method of ExpNegativeImageFilter in order to support a procedural API
36973
itk::simple::ExpNegativeImageFilter for the object oriented interface
36978
%feature("docstring") itk::simple::Extract "
36980
Decrease the image size by cropping the image to the selected region
36984
This function directly calls the execute method of ExtractImageFilter in order to support a procedural API
36988
itk::simple::ExtractImageFilter for the object oriented interface
36993
%feature("docstring") itk::simple::FastApproximateRank "
36995
A separable rank filter.
36998
This function directly calls the execute method of FastApproximateRankImageFilter in order to support a procedural API
37002
itk::simple::FastApproximateRankImageFilter for the object oriented interface
37007
%feature("docstring") itk::simple::FastMarching "
37009
Solve an Eikonal equation using Fast Marching.
37012
This function directly calls the execute method of FastMarchingImageFilter in order to support a procedural API
37016
itk::simple::FastMarchingImageFilter for the object oriented interface
37021
%feature("docstring") itk::simple::FastMarchingBase "
37023
itk::simple::FastMarchingBaseImageFilter Functional Interface
37025
This function directly calls the execute method of FastMarchingBaseImageFilter in order to support a fully functional API
37029
%feature("docstring") itk::simple::FastMarchingUpwindGradient "
37031
Generates the upwind gradient field of fast marching arrival times.
37034
This function directly calls the execute method of FastMarchingUpwindGradientImageFilter in order to support a procedural API
37038
itk::simple::FastMarchingUpwindGradientImageFilter for the object oriented interface
37043
%feature("docstring") itk::simple::FFTConvolution "
37045
Convolve a given image with an arbitrary image kernel using
37046
multiplication in the Fourier domain.
37049
This function directly calls the execute method of FFTConvolutionImageFilter in order to support a procedural API
37053
itk::simple::FFTConvolutionImageFilter for the object oriented interface
37058
%feature("docstring") itk::simple::FFTNormalizedCorrelation "
37060
Calculate normalized cross correlation using FFTs.
37063
This function directly calls the execute method of FFTNormalizedCorrelationImageFilter in order to support a procedural API
37067
itk::simple::FFTNormalizedCorrelationImageFilter for the object oriented interface
37072
%feature("docstring") itk::simple::FFTPad "
37074
Pad an image to make it suitable for an FFT transformation.
37077
This function directly calls the execute method of FFTPadImageFilter in order to support a procedural API
37081
itk::simple::FFTPadImageFilter for the object oriented interface
37086
%feature("docstring") itk::simple::FFTShift "
37088
Shift the zero-frequency components of a Fourier transform to the
37089
center of the image.
37092
This function directly calls the execute method of FFTShiftImageFilter in order to support a procedural API
37096
itk::simple::FFTShiftImageFilter for the object oriented interface
37101
%feature("docstring") itk::simple::Flip "
37103
Flips an image across user specified axes.
37106
This function directly calls the execute method of FlipImageFilter in order to support a procedural API
37110
itk::simple::FlipImageFilter for the object oriented interface
37115
%feature("docstring") itk::simple::ForwardFFT "
37117
Base class for forward Fast Fourier Transform .
37120
This function directly calls the execute method of ForwardFFTImageFilter in order to support a procedural API
37124
itk::simple::ForwardFFTImageFilter for the object oriented interface
37129
%feature("docstring") itk::simple::GaborSource "
37131
Generate an n-dimensional image of a Gabor filter.
37134
This function directly calls the execute method of GaborImageSource in order to support a procedural API
37138
itk::simple::GaborImageSource for the object oriented interface
37143
%feature("docstring") itk::simple::GaussianSource "
37145
Generate an n-dimensional image of a Gaussian.
37148
This function directly calls the execute method of GaussianImageSource in order to support a procedural API
37152
itk::simple::GaussianImageSource for the object oriented interface
37157
%feature("docstring") itk::simple::GeodesicActiveContourLevelSet "
37159
Segments structures in images based on a user supplied edge potential
37163
This function directly calls the execute method of GeodesicActiveContourLevelSetImageFilter in order to support a procedural API
37167
itk::simple::GeodesicActiveContourLevelSetImageFilter for the object oriented interface
37172
%feature("docstring") itk::simple::GetImageFromVectorImage "
37174
A utility method to help convert between itk image types efficiently.
37178
%feature("docstring") itk::simple::GetPixelIDValueAsString "
37181
%feature("docstring") itk::simple::GetPixelIDValueAsString "
37184
%feature("docstring") itk::simple::GetPixelIDValueFromString "
37186
Function mapping enumeration names in std::string to values.
37189
This function is intended for use by the R bindings. R stores the
37190
enumeration values using the names : \"sitkUnkown\", \"sitkUInt8\",
37191
etc from PixelIDValueEnum above. This function is used to provide the
37192
integer values using calls like:
37194
val = GetPixelIDValueFromString(\"sitkInt32\")
37196
If the pixel type has not been instantiated then the sitkUnknown value
37197
(-1) will be returned. If the pixel type string is not recognised
37198
(i.e. is not in the set of tested names) then the return value is -99.
37199
The idea is to provide a warning (via the R package) if this function
37200
needs to be updated to match changes to PixelIDValueEnum - i.e. if a
37201
new pixel type is added.
37205
%feature("docstring") itk::simple::GetVectorImageFromImage "
37208
%feature("docstring") itk::simple::GetVectorImageFromImage "
37211
%feature("docstring") itk::simple::Gradient "
37213
Computes the gradient of an image using directional derivatives.
37216
This function directly calls the execute method of GradientImageFilter in order to support a procedural API
37220
itk::simple::GradientImageFilter for the object oriented interface
37225
%feature("docstring") itk::simple::GradientAnisotropicDiffusion "
37227
itk::simple::GradientAnisotropicDiffusionImageFilter Procedural Interface
37230
This function directly calls the execute method of GradientAnisotropicDiffusionImageFilter in order to support a procedural API
37234
itk::simple::GradientAnisotropicDiffusionImageFilter for the object oriented interface
37239
%feature("docstring") itk::simple::GradientMagnitude "
37241
Computes the gradient magnitude of an image region at each pixel.
37244
This function directly calls the execute method of GradientMagnitudeImageFilter in order to support a procedural API
37248
itk::simple::GradientMagnitudeImageFilter for the object oriented interface
37253
%feature("docstring") itk::simple::GradientMagnitudeRecursiveGaussian "
37255
Computes the Magnitude of the Gradient of an image by convolution with
37256
the first derivative of a Gaussian.
37259
This function directly calls the execute method of GradientMagnitudeRecursiveGaussianImageFilter in order to support a procedural API
37263
itk::simple::GradientMagnitudeRecursiveGaussianImageFilter for the object oriented interface
37268
%feature("docstring") itk::simple::GradientRecursiveGaussian "
37270
Computes the gradient of an image by convolution with the first
37271
derivative of a Gaussian.
37274
This function directly calls the execute method of GradientRecursiveGaussianImageFilter in order to support a procedural API
37278
itk::simple::GradientRecursiveGaussianImageFilter for the object oriented interface
37283
%feature("docstring") itk::simple::GrayscaleConnectedClosing "
37285
Enhance pixels associated with a dark object (identified by a seed
37286
pixel) where the dark object is surrounded by a brigher object.
37289
This function directly calls the execute method of GrayscaleConnectedClosingImageFilter in order to support a procedural API
37293
itk::simple::GrayscaleConnectedClosingImageFilter for the object oriented interface
37298
%feature("docstring") itk::simple::GrayscaleConnectedOpening "
37300
Enhance pixels associated with a bright object (identified by a seed
37301
pixel) where the bright object is surrounded by a darker object.
37304
This function directly calls the execute method of GrayscaleConnectedOpeningImageFilter in order to support a procedural API
37308
itk::simple::GrayscaleConnectedOpeningImageFilter for the object oriented interface
37313
%feature("docstring") itk::simple::GrayscaleDilate "
37315
itk::simple::GrayscaleDilateImageFilter Functional Interface
37317
This function directly calls the execute method of GrayscaleDilateImageFilter in order to support a fully functional API
37321
%feature("docstring") itk::simple::GrayscaleDilate "
37323
itk::simple::GrayscaleDilateImageFilter Functional Interface
37325
This function directly calls the execute method of GrayscaleDilateImageFilter in order to support a fully functional API
37329
%feature("docstring") itk::simple::GrayscaleErode "
37331
itk::simple::GrayscaleErodeImageFilter Functional Interface
37333
This function directly calls the execute method of GrayscaleErodeImageFilter in order to support a fully functional API
37337
%feature("docstring") itk::simple::GrayscaleErode "
37339
itk::simple::GrayscaleErodeImageFilter Functional Interface
37341
This function directly calls the execute method of GrayscaleErodeImageFilter in order to support a fully functional API
37345
%feature("docstring") itk::simple::GrayscaleFillhole "
37347
Remove local minima not connected to the boundary of the image.
37350
This function directly calls the execute method of GrayscaleFillholeImageFilter in order to support a procedural API
37354
itk::simple::GrayscaleFillholeImageFilter for the object oriented interface
37359
%feature("docstring") itk::simple::GrayscaleGeodesicDilate "
37361
geodesic gray scale dilation of an image
37364
This function directly calls the execute method of GrayscaleGeodesicDilateImageFilter in order to support a procedural API
37368
itk::simple::GrayscaleGeodesicDilateImageFilter for the object oriented interface
37373
%feature("docstring") itk::simple::GrayscaleGeodesicErode "
37375
geodesic gray scale erosion of an image
37378
This function directly calls the execute method of GrayscaleGeodesicErodeImageFilter in order to support a procedural API
37382
itk::simple::GrayscaleGeodesicErodeImageFilter for the object oriented interface
37387
%feature("docstring") itk::simple::GrayscaleGrindPeak "
37389
Remove local maxima not connected to the boundary of the image.
37392
This function directly calls the execute method of GrayscaleGrindPeakImageFilter in order to support a procedural API
37396
itk::simple::GrayscaleGrindPeakImageFilter for the object oriented interface
37401
%feature("docstring") itk::simple::GrayscaleMorphologicalClosing "
37403
itk::simple::GrayscaleMorphologicalClosingImageFilter Functional Interface
37405
This function directly calls the execute method of GrayscaleMorphologicalClosingImageFilter in order to support a fully functional API
37409
%feature("docstring") itk::simple::GrayscaleMorphologicalClosing "
37411
itk::simple::GrayscaleMorphologicalClosingImageFilter Functional Interface
37413
This function directly calls the execute method of GrayscaleMorphologicalClosingImageFilter in order to support a fully functional API
37417
%feature("docstring") itk::simple::GrayscaleMorphologicalOpening "
37419
itk::simple::GrayscaleMorphologicalOpeningImageFilter Functional Interface
37421
This function directly calls the execute method of GrayscaleMorphologicalOpeningImageFilter in order to support a fully functional API
37425
%feature("docstring") itk::simple::GrayscaleMorphologicalOpening "
37427
itk::simple::GrayscaleMorphologicalOpeningImageFilter Functional Interface
37429
This function directly calls the execute method of GrayscaleMorphologicalOpeningImageFilter in order to support a fully functional API
37433
%feature("docstring") itk::simple::Greater "
37435
Implements pixel-wise generic operation of two images, or of an image
37439
This function directly calls the execute method of GreaterImageFilter in order to support a procedural API
37443
itk::simple::GreaterImageFilter for the object oriented interface
37448
%feature("docstring") itk::simple::Greater "
37451
%feature("docstring") itk::simple::Greater "
37454
%feature("docstring") itk::simple::GreaterEqual "
37456
Implements pixel-wise generic operation of two images, or of an image
37460
This function directly calls the execute method of GreaterEqualImageFilter in order to support a procedural API
37464
itk::simple::GreaterEqualImageFilter for the object oriented interface
37469
%feature("docstring") itk::simple::GreaterEqual "
37472
%feature("docstring") itk::simple::GreaterEqual "
37475
%feature("docstring") itk::simple::GridSource "
37477
Generate an n-dimensional image of a grid.
37480
This function directly calls the execute method of GridImageSource in order to support a procedural API
37484
itk::simple::GridImageSource for the object oriented interface
37489
%feature("docstring") itk::simple::HalfHermitianToRealInverseFFT "
37491
Base class for specialized complex-to-real inverse Fast Fourier Transform .
37494
This function directly calls the execute method of HalfHermitianToRealInverseFFTImageFilter in order to support a procedural API
37498
itk::simple::HalfHermitianToRealInverseFFTImageFilter for the object oriented interface
37503
%feature("docstring") itk::simple::Hash "
37506
%feature("docstring") itk::simple::HConcave "
37508
Identify local minima whose depth below the baseline is greater than
37512
This function directly calls the execute method of HConcaveImageFilter in order to support a procedural API
37516
itk::simple::HConcaveImageFilter for the object oriented interface
37521
%feature("docstring") itk::simple::HConvex "
37523
Identify local maxima whose height above the baseline is greater than
37527
This function directly calls the execute method of HConvexImageFilter in order to support a procedural API
37531
itk::simple::HConvexImageFilter for the object oriented interface
37536
%feature("docstring") itk::simple::HistogramMatching "
37538
Normalize the grayscale values between two images by histogram
37542
This function directly calls the execute method of HistogramMatchingImageFilter in order to support a procedural API
37546
itk::simple::HistogramMatchingImageFilter for the object oriented interface
37551
%feature("docstring") itk::simple::HMaxima "
37553
Suppress local maxima whose height above the baseline is less than h.
37556
This function directly calls the execute method of HMaximaImageFilter in order to support a procedural API
37560
itk::simple::HMaximaImageFilter for the object oriented interface
37565
%feature("docstring") itk::simple::HMinima "
37567
Suppress local minima whose depth below the baseline is less than h.
37570
This function directly calls the execute method of HMinimaImageFilter in order to support a procedural API
37574
itk::simple::HMinimaImageFilter for the object oriented interface
37579
%feature("docstring") itk::simple::HuangThreshold "
37581
Threshold an image using the Huang Threshold.
37584
This function directly calls the execute method of HuangThresholdImageFilter in order to support a procedural API
37588
itk::simple::HuangThresholdImageFilter for the object oriented interface
37593
%feature("docstring") itk::simple::HuangThreshold "
37596
%feature("docstring") itk::simple::ImportAsDouble "
37599
%feature("docstring") itk::simple::ImportAsFloat "
37602
%feature("docstring") itk::simple::ImportAsInt16 "
37605
%feature("docstring") itk::simple::ImportAsInt32 "
37608
%feature("docstring") itk::simple::ImportAsInt64 "
37611
%feature("docstring") itk::simple::ImportAsInt8 "
37614
%feature("docstring") itk::simple::ImportAsUInt16 "
37617
%feature("docstring") itk::simple::ImportAsUInt32 "
37620
%feature("docstring") itk::simple::ImportAsUInt64 "
37623
%feature("docstring") itk::simple::ImportAsUInt8 "
37626
%feature("docstring") itk::simple::IntensityWindowing "
37628
Applies a linear transformation to the intensity levels of the input Image that are inside a user-defined interval. Values below this interval
37629
are mapped to a constant. Values over the interval are mapped to
37633
This function directly calls the execute method of IntensityWindowingImageFilter in order to support a procedural API
37637
itk::simple::IntensityWindowingImageFilter for the object oriented interface
37642
%feature("docstring") itk::simple::IntermodesThreshold "
37644
Threshold an image using the Intermodes Threshold.
37647
This function directly calls the execute method of IntermodesThresholdImageFilter in order to support a procedural API
37651
itk::simple::IntermodesThresholdImageFilter for the object oriented interface
37656
%feature("docstring") itk::simple::IntermodesThreshold "
37659
%feature("docstring") itk::simple::InverseDeconvolution "
37661
The direct linear inverse deconvolution filter.
37664
This function directly calls the execute method of InverseDeconvolutionImageFilter in order to support a procedural API
37668
itk::simple::InverseDeconvolutionImageFilter for the object oriented interface
37673
%feature("docstring") itk::simple::InverseDisplacementField "
37675
Computes the inverse of a displacement field.
37678
This function directly calls the execute method of InverseDisplacementFieldImageFilter in order to support a procedural API
37682
itk::simple::InverseDisplacementFieldImageFilter for the object oriented interface
37687
%feature("docstring") itk::simple::InverseFFT "
37689
Base class for inverse Fast Fourier Transform .
37692
This function directly calls the execute method of InverseFFTImageFilter in order to support a procedural API
37696
itk::simple::InverseFFTImageFilter for the object oriented interface
37701
%feature("docstring") itk::simple::InvertDisplacementField "
37703
Iteratively estimate the inverse field of a displacement field.
37706
This function directly calls the execute method of InvertDisplacementFieldImageFilter in order to support a procedural API
37710
itk::simple::InvertDisplacementFieldImageFilter for the object oriented interface
37715
%feature("docstring") itk::simple::InvertIntensity "
37717
Invert the intensity of an image.
37720
This function directly calls the execute method of InvertIntensityImageFilter in order to support a procedural API
37724
itk::simple::InvertIntensityImageFilter for the object oriented interface
37729
%feature("docstring") itk::simple::IsoContourDistance "
37731
Compute an approximate distance from an interpolated isocontour to the
37735
This function directly calls the execute method of IsoContourDistanceImageFilter in order to support a procedural API
37739
itk::simple::IsoContourDistanceImageFilter for the object oriented interface
37744
%feature("docstring") itk::simple::IsoDataThreshold "
37746
Threshold an image using the IsoData Threshold.
37749
This function directly calls the execute method of IsoDataThresholdImageFilter in order to support a procedural API
37753
itk::simple::IsoDataThresholdImageFilter for the object oriented interface
37758
%feature("docstring") itk::simple::IsoDataThreshold "
37761
%feature("docstring") itk::simple::IsolatedConnected "
37763
Label pixels that are connected to one set of seeds but not another.
37766
This function directly calls the execute method of IsolatedConnectedImageFilter in order to support a procedural API
37770
itk::simple::IsolatedConnectedImageFilter for the object oriented interface
37775
%feature("docstring") itk::simple::IsolatedWatershed "
37777
Isolate watershed basins using two seeds.
37780
This function directly calls the execute method of IsolatedWatershedImageFilter in order to support a procedural API
37784
itk::simple::IsolatedWatershedImageFilter for the object oriented interface
37789
%feature("docstring") itk::simple::IterativeInverseDisplacementField "
37791
Computes the inverse of a displacement field.
37794
This function directly calls the execute method of IterativeInverseDisplacementFieldImageFilter in order to support a procedural API
37798
itk::simple::IterativeInverseDisplacementFieldImageFilter for the object oriented interface
37803
%feature("docstring") itk::simple::KittlerIllingworthThreshold "
37805
Threshold an image using the KittlerIllingworth Threshold.
37808
This function directly calls the execute method of KittlerIllingworthThresholdImageFilter in order to support a procedural API
37812
itk::simple::KittlerIllingworthThresholdImageFilter for the object oriented interface
37817
%feature("docstring") itk::simple::KittlerIllingworthThreshold "
37820
%feature("docstring") itk::simple::LabelContour "
37822
Labels the pixels on the border of the objects in a labeled image.
37825
This function directly calls the execute method of LabelContourImageFilter in order to support a procedural API
37829
itk::simple::LabelContourImageFilter for the object oriented interface
37834
%feature("docstring") itk::simple::LabelImageToLabelMap "
37836
convert a labeled image to a label collection image
37839
This function directly calls the execute method of LabelImageToLabelMapFilter in order to support a procedural API
37843
itk::simple::LabelImageToLabelMapFilter for the object oriented interface
37848
%feature("docstring") itk::simple::LabelMapContourOverlay "
37850
Apply a colormap to the contours (outlines) of each object in a label
37851
map and superimpose it on top of the feature image.
37854
This function directly calls the execute method of LabelMapContourOverlayImageFilter in order to support a procedural API
37858
itk::simple::LabelMapContourOverlayImageFilter for the object oriented interface
37863
%feature("docstring") itk::simple::LabelMapMask "
37865
Mask and image with a LabelMap .
37868
This function directly calls the execute method of LabelMapMaskImageFilter in order to support a procedural API
37872
itk::simple::LabelMapMaskImageFilter for the object oriented interface
37877
%feature("docstring") itk::simple::LabelMapOverlay "
37879
Apply a colormap to a label map and superimpose it on an image.
37882
This function directly calls the execute method of LabelMapOverlayImageFilter in order to support a procedural API
37886
itk::simple::LabelMapOverlayImageFilter for the object oriented interface
37891
%feature("docstring") itk::simple::LabelMapToBinary "
37893
Convert a LabelMap to a binary image.
37896
This function directly calls the execute method of LabelMapToBinaryImageFilter in order to support a procedural API
37900
itk::simple::LabelMapToBinaryImageFilter for the object oriented interface
37905
%feature("docstring") itk::simple::LabelMapToLabel "
37907
Converts a LabelMap to a labeled image.
37910
This function directly calls the execute method of LabelMapToLabelImageFilter in order to support a procedural API
37914
itk::simple::LabelMapToLabelImageFilter for the object oriented interface
37919
%feature("docstring") itk::simple::LabelMapToRGB "
37921
Convert a LabelMap to a colored image.
37924
This function directly calls the execute method of LabelMapToRGBImageFilter in order to support a procedural API
37928
itk::simple::LabelMapToRGBImageFilter for the object oriented interface
37933
%feature("docstring") itk::simple::LabelOverlay "
37935
Apply a colormap to a label image and put it on top of the input
37939
This function directly calls the execute method of LabelOverlayImageFilter in order to support a procedural API
37943
itk::simple::LabelOverlayImageFilter for the object oriented interface
37948
%feature("docstring") itk::simple::LabelToRGB "
37950
Apply a colormap to a label image.
37953
This function directly calls the execute method of LabelToRGBImageFilter in order to support a procedural API
37957
itk::simple::LabelToRGBImageFilter for the object oriented interface
37962
%feature("docstring") itk::simple::LabelUniqueLabelMap "
37964
Make sure that the objects are not overlapping.
37967
This function directly calls the execute method of LabelUniqueLabelMapFilter in order to support a procedural API
37971
itk::simple::LabelUniqueLabelMapFilter for the object oriented interface
37976
%feature("docstring") itk::simple::LandmarkBasedTransformInitializer "
37978
itk::simple::LandmarkBasedTransformInitializerFilter Procedural Interface
37981
This function directly calls the execute method of LandmarkBasedTransformInitializerFilter in order to support a procedural API
37985
itk::simple::LandmarkBasedTransformInitializerFilter for the object oriented interface
37990
%feature("docstring") itk::simple::LandweberDeconvolution "
37992
Deconvolve an image using the Landweber deconvolution algorithm.
37995
This function directly calls the execute method of LandweberDeconvolutionImageFilter in order to support a procedural API
37999
itk::simple::LandweberDeconvolutionImageFilter for the object oriented interface
38004
%feature("docstring") itk::simple::Laplacian "
38006
itk::simple::LaplacianImageFilter Procedural Interface
38009
This function directly calls the execute method of LaplacianImageFilter in order to support a procedural API
38013
itk::simple::LaplacianImageFilter for the object oriented interface
38018
%feature("docstring") itk::simple::LaplacianRecursiveGaussian "
38020
Computes the Laplacian of Gaussian (LoG) of an image.
38023
This function directly calls the execute method of LaplacianRecursiveGaussianImageFilter in order to support a procedural API
38027
itk::simple::LaplacianRecursiveGaussianImageFilter for the object oriented interface
38032
%feature("docstring") itk::simple::LaplacianSegmentationLevelSet "
38034
Segments structures in images based on a second derivative image
38038
This function directly calls the execute method of LaplacianSegmentationLevelSetImageFilter in order to support a procedural API
38042
itk::simple::LaplacianSegmentationLevelSetImageFilter for the object oriented interface
38047
%feature("docstring") itk::simple::LaplacianSharpening "
38049
This filter sharpens an image using a Laplacian. LaplacianSharpening
38050
highlights regions of rapid intensity change and therefore highlights
38051
or enhances the edges. The result is an image that appears more in
38055
This function directly calls the execute method of LaplacianSharpeningImageFilter in order to support a procedural API
38059
itk::simple::LaplacianSharpeningImageFilter for the object oriented interface
38064
%feature("docstring") itk::simple::Less "
38066
Implements pixel-wise generic operation of two images, or of an image
38070
This function directly calls the execute method of LessImageFilter in order to support a procedural API
38074
itk::simple::LessImageFilter for the object oriented interface
38079
%feature("docstring") itk::simple::Less "
38082
%feature("docstring") itk::simple::Less "
38085
%feature("docstring") itk::simple::LessEqual "
38087
Implements pixel-wise generic operation of two images, or of an image
38091
This function directly calls the execute method of LessEqualImageFilter in order to support a procedural API
38095
itk::simple::LessEqualImageFilter for the object oriented interface
38100
%feature("docstring") itk::simple::LessEqual "
38103
%feature("docstring") itk::simple::LessEqual "
38106
%feature("docstring") itk::simple::LiThreshold "
38108
Threshold an image using the Li Threshold.
38111
This function directly calls the execute method of LiThresholdImageFilter in order to support a procedural API
38115
itk::simple::LiThresholdImageFilter for the object oriented interface
38120
%feature("docstring") itk::simple::LiThreshold "
38123
%feature("docstring") itk::simple::Log "
38125
Computes the log() of each pixel.
38128
This function directly calls the execute method of LogImageFilter in order to support a procedural API
38132
itk::simple::LogImageFilter for the object oriented interface
38137
%feature("docstring") itk::simple::Log10 "
38139
Computes the log10 of each pixel.
38142
This function directly calls the execute method of Log10ImageFilter in order to support a procedural API
38146
itk::simple::Log10ImageFilter for the object oriented interface
38151
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplex "
38153
Implements pixel-wise conversion of magnitude and phase data into
38157
This function directly calls the execute method of MagnitudeAndPhaseToComplexImageFilter in order to support a procedural API
38161
itk::simple::MagnitudeAndPhaseToComplexImageFilter for the object oriented interface
38166
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplex "
38169
%feature("docstring") itk::simple::MagnitudeAndPhaseToComplex "
38172
%feature("docstring") itk::simple::Mask "
38174
Mask an image with a mask.
38177
This function directly calls the execute method of MaskImageFilter in order to support a procedural API
38181
itk::simple::MaskImageFilter for the object oriented interface
38186
%feature("docstring") itk::simple::MaskedFFTNormalizedCorrelation "
38188
Calculate masked normalized cross correlation using FFTs.
38191
This function directly calls the execute method of MaskedFFTNormalizedCorrelationImageFilter in order to support a procedural API
38195
itk::simple::MaskedFFTNormalizedCorrelationImageFilter for the object oriented interface
38200
%feature("docstring") itk::simple::MaskNegated "
38202
Mask an image with the negative of a mask.
38205
This function directly calls the execute method of MaskNegatedImageFilter in order to support a procedural API
38209
itk::simple::MaskNegatedImageFilter for the object oriented interface
38214
%feature("docstring") itk::simple::Maximum "
38216
Implements a pixel-wise operator Max(a,b) between two images.
38219
This function directly calls the execute method of MaximumImageFilter in order to support a procedural API
38223
itk::simple::MaximumImageFilter for the object oriented interface
38228
%feature("docstring") itk::simple::Maximum "
38231
%feature("docstring") itk::simple::Maximum "
38234
%feature("docstring") itk::simple::MaximumEntropyThreshold "
38236
Threshold an image using the MaximumEntropy Threshold.
38239
This function directly calls the execute method of MaximumEntropyThresholdImageFilter in order to support a procedural API
38243
itk::simple::MaximumEntropyThresholdImageFilter for the object oriented interface
38248
%feature("docstring") itk::simple::MaximumEntropyThreshold "
38251
%feature("docstring") itk::simple::MaximumProjection "
38253
Maximum projection.
38256
This function directly calls the execute method of MaximumProjectionImageFilter in order to support a procedural API
38260
itk::simple::MaximumProjectionImageFilter for the object oriented interface
38265
%feature("docstring") itk::simple::Mean "
38267
Applies an averaging filter to an image.
38270
This function directly calls the execute method of MeanImageFilter in order to support a procedural API
38274
itk::simple::MeanImageFilter for the object oriented interface
38279
%feature("docstring") itk::simple::MeanProjection "
38284
This function directly calls the execute method of MeanProjectionImageFilter in order to support a procedural API
38288
itk::simple::MeanProjectionImageFilter for the object oriented interface
38293
%feature("docstring") itk::simple::Median "
38295
Applies a median filter to an image.
38298
This function directly calls the execute method of MedianImageFilter in order to support a procedural API
38302
itk::simple::MedianImageFilter for the object oriented interface
38307
%feature("docstring") itk::simple::MedianProjection "
38312
This function directly calls the execute method of MedianProjectionImageFilter in order to support a procedural API
38316
itk::simple::MedianProjectionImageFilter for the object oriented interface
38321
%feature("docstring") itk::simple::Minimum "
38323
Implements a pixel-wise operator Min(a,b) between two images.
38326
This function directly calls the execute method of MinimumImageFilter in order to support a procedural API
38330
itk::simple::MinimumImageFilter for the object oriented interface
38335
%feature("docstring") itk::simple::Minimum "
38338
%feature("docstring") itk::simple::Minimum "
38341
%feature("docstring") itk::simple::MinimumProjection "
38343
Minimum projection.
38346
This function directly calls the execute method of MinimumProjectionImageFilter in order to support a procedural API
38350
itk::simple::MinimumProjectionImageFilter for the object oriented interface
38355
%feature("docstring") itk::simple::MinMaxCurvatureFlow "
38357
Denoise an image using min/max curvature flow.
38360
This function directly calls the execute method of MinMaxCurvatureFlowImageFilter in order to support a procedural API
38364
itk::simple::MinMaxCurvatureFlowImageFilter for the object oriented interface
38369
%feature("docstring") itk::simple::MirrorPad "
38371
Increase the image size by padding with replicants of the input image
38375
This function directly calls the execute method of MirrorPadImageFilter in order to support a procedural API
38379
itk::simple::MirrorPadImageFilter for the object oriented interface
38384
%feature("docstring") itk::simple::Modulus "
38386
Computes the modulus (x % dividend) pixel-wise.
38389
This function directly calls the execute method of ModulusImageFilter in order to support a procedural API
38393
itk::simple::ModulusImageFilter for the object oriented interface
38398
%feature("docstring") itk::simple::Modulus "
38401
%feature("docstring") itk::simple::Modulus "
38404
%feature("docstring") itk::simple::MomentsThreshold "
38406
Threshold an image using the Moments Threshold.
38409
This function directly calls the execute method of MomentsThresholdImageFilter in order to support a procedural API
38413
itk::simple::MomentsThresholdImageFilter for the object oriented interface
38418
%feature("docstring") itk::simple::MomentsThreshold "
38421
%feature("docstring") itk::simple::MorphologicalGradient "
38423
itk::simple::MorphologicalGradientImageFilter Functional Interface
38425
This function directly calls the execute method of MorphologicalGradientImageFilter in order to support a fully functional API
38429
%feature("docstring") itk::simple::MorphologicalGradient "
38431
itk::simple::MorphologicalGradientImageFilter Functional Interface
38433
This function directly calls the execute method of MorphologicalGradientImageFilter in order to support a fully functional API
38437
%feature("docstring") itk::simple::MorphologicalWatershed "
38439
Watershed segmentation implementation with morphogical operators.
38442
This function directly calls the execute method of MorphologicalWatershedImageFilter in order to support a procedural API
38446
itk::simple::MorphologicalWatershedImageFilter for the object oriented interface
38451
%feature("docstring") itk::simple::MorphologicalWatershedFromMarkers "
38453
Morphological watershed transform from markers.
38456
This function directly calls the execute method of MorphologicalWatershedFromMarkersImageFilter in order to support a procedural API
38460
itk::simple::MorphologicalWatershedFromMarkersImageFilter for the object oriented interface
38465
%feature("docstring") itk::simple::Multiply "
38467
Pixel-wise multiplication of two images.
38470
This function directly calls the execute method of MultiplyImageFilter in order to support a procedural API
38474
itk::simple::MultiplyImageFilter for the object oriented interface
38479
%feature("docstring") itk::simple::Multiply "
38482
%feature("docstring") itk::simple::Multiply "
38485
%feature("docstring") itk::simple::N4BiasFieldCorrection "
38487
Implementation of the N4 bias field correction algorithm.
38490
This function directly calls the execute method of N4BiasFieldCorrectionImageFilter in order to support a procedural API
38494
itk::simple::N4BiasFieldCorrectionImageFilter for the object oriented interface
38499
%feature("docstring") itk::simple::NeighborhoodConnected "
38501
itk::simple::NeighborhoodConnectedImageFilter Functional Interface
38503
This function directly calls the execute method of NeighborhoodConnectedImageFilter in order to support a fully functional API
38507
%feature("docstring") itk::simple::Noise "
38509
Calculate the local noise in an image.
38512
This function directly calls the execute method of NoiseImageFilter in order to support a procedural API
38516
itk::simple::NoiseImageFilter for the object oriented interface
38521
%feature("docstring") itk::simple::Normalize "
38523
Normalize an image by setting its mean to zero and variance to one.
38526
This function directly calls the execute method of NormalizeImageFilter in order to support a procedural API
38530
itk::simple::NormalizeImageFilter for the object oriented interface
38535
%feature("docstring") itk::simple::NormalizedCorrelation "
38537
Computes the normalized correlation of an image and a template.
38540
This function directly calls the execute method of NormalizedCorrelationImageFilter in order to support a procedural API
38544
itk::simple::NormalizedCorrelationImageFilter for the object oriented interface
38549
%feature("docstring") itk::simple::NormalizeToConstant "
38551
Scales image pixel intensities to make the sum of all pixels equal a
38552
user-defined constant.
38555
This function directly calls the execute method of NormalizeToConstantImageFilter in order to support a procedural API
38559
itk::simple::NormalizeToConstantImageFilter for the object oriented interface
38564
%feature("docstring") itk::simple::Not "
38566
Implements the NOT logical operator pixel-wise on an image.
38569
This function directly calls the execute method of NotImageFilter in order to support a procedural API
38573
itk::simple::NotImageFilter for the object oriented interface
38578
%feature("docstring") itk::simple::NotEqual "
38580
Implements pixel-wise generic operation of two images, or of an image
38584
This function directly calls the execute method of NotEqualImageFilter in order to support a procedural API
38588
itk::simple::NotEqualImageFilter for the object oriented interface
38593
%feature("docstring") itk::simple::NotEqual "
38596
%feature("docstring") itk::simple::NotEqual "
38599
%feature("docstring") itk::simple::OpeningByReconstruction "
38601
itk::simple::OpeningByReconstructionImageFilter Functional Interface
38603
This function directly calls the execute method of OpeningByReconstructionImageFilter in order to support a fully functional API
38607
%feature("docstring") itk::simple::OpeningByReconstruction "
38609
itk::simple::OpeningByReconstructionImageFilter Functional Interface
38611
This function directly calls the execute method of OpeningByReconstructionImageFilter in order to support a fully functional API
38615
%feature("docstring") itk::simple::Or "
38617
Implements the OR bitwise operator pixel-wise between two images.
38620
This function directly calls the execute method of OrImageFilter in order to support a procedural API
38624
itk::simple::OrImageFilter for the object oriented interface
38629
%feature("docstring") itk::simple::Or "
38632
%feature("docstring") itk::simple::Or "
38635
%feature("docstring") itk::simple::OtsuMultipleThresholds "
38637
Threshold an image using multiple Otsu Thresholds.
38640
This function directly calls the execute method of OtsuMultipleThresholdsImageFilter in order to support a procedural API
38644
itk::simple::OtsuMultipleThresholdsImageFilter for the object oriented interface
38649
%feature("docstring") itk::simple::OtsuThreshold "
38651
Threshold an image using the Otsu Threshold.
38654
This function directly calls the execute method of OtsuThresholdImageFilter in order to support a procedural API
38658
itk::simple::OtsuThresholdImageFilter for the object oriented interface
38663
%feature("docstring") itk::simple::OtsuThreshold "
38666
%feature("docstring") itk::simple::Paste "
38668
Paste an image into another image.
38671
This function directly calls the execute method of PasteImageFilter in order to support a procedural API
38675
itk::simple::PasteImageFilter for the object oriented interface
38680
%feature("docstring") itk::simple::PatchBasedDenoising "
38682
itk::simple::PatchBasedDenoisingImageFilter Procedural Interface
38685
This function directly calls the execute method of PatchBasedDenoisingImageFilter in order to support a procedural API
38689
itk::simple::PatchBasedDenoisingImageFilter for the object oriented interface
38694
%feature("docstring") itk::simple::PatchBasedDenoising "
38697
%feature("docstring") itk::simple::PermuteAxes "
38699
Permutes the image axes according to a user specified order.
38702
This function directly calls the execute method of PermuteAxesImageFilter in order to support a procedural API
38706
itk::simple::PermuteAxesImageFilter for the object oriented interface
38711
%feature("docstring") itk::simple::PhysicalPointSource "
38713
Generate an image of the physical locations of each pixel.
38716
This function directly calls the execute method of PhysicalPointImageSource in order to support a procedural API
38720
itk::simple::PhysicalPointImageSource for the object oriented interface
38725
%feature("docstring") itk::simple::Pow "
38727
Computes the powers of 2 images.
38730
This function directly calls the execute method of PowImageFilter in order to support a procedural API
38734
itk::simple::PowImageFilter for the object oriented interface
38739
%feature("docstring") itk::simple::Pow "
38742
%feature("docstring") itk::simple::Pow "
38745
%feature("docstring") itk::simple::ProjectedLandweberDeconvolution "
38747
Deconvolve an image using the projected Landweber deconvolution
38751
This function directly calls the execute method of ProjectedLandweberDeconvolutionImageFilter in order to support a procedural API
38755
itk::simple::ProjectedLandweberDeconvolutionImageFilter for the object oriented interface
38760
%feature("docstring") itk::simple::Rank "
38762
Rank filter of a greyscale image.
38765
This function directly calls the execute method of RankImageFilter in order to support a procedural API
38769
itk::simple::RankImageFilter for the object oriented interface
38774
%feature("docstring") itk::simple::ReadImage "
38776
ReadImage is a procedural interface to the ImageFileReader class which is convenient for most image reading tasks.
38779
For more complicated use cases such as requiring loading of all tags,
38780
including private ones, from a DICOM file the object oriented
38781
interface should be used. The reader can be explicitly set to load all
38782
tags (LoadPrivateTagsOn()).
38786
%feature("docstring") itk::simple::ReadImage "
38788
ReadImage is a procedural interface to the ImageSeriesReader class which is convenient for most image reading tasks.
38791
Note that when reading a series of images that have meta-data
38792
associated with them (e.g. a DICOM series) the resulting image will
38793
have an empty meta-data dictionary. It is possible to programmatically
38794
add a meta-data dictionary to the compounded image by reading in one
38795
or more images from the series using the ImageFileReader class,
38796
analyzing the meta-dictionary associated with each of those images and
38797
creating one that is relevant for the compounded image.
38801
itk::simple::ImageFileReader for reading a single file
38806
%feature("docstring") itk::simple::ReadTransform "
38809
%feature("docstring") itk::simple::RealAndImaginaryToComplex "
38811
ComposeImageFilter combine several scalar images into a multicomponent image.
38814
This function directly calls the execute method of RealAndImaginaryToComplexImageFilter in order to support a procedural API
38818
itk::simple::RealAndImaginaryToComplexImageFilter for the object oriented interface
38823
%feature("docstring") itk::simple::RealToHalfHermitianForwardFFT "
38825
Base class for specialized real-to-complex forward Fast Fourier Transform .
38828
This function directly calls the execute method of RealToHalfHermitianForwardFFTImageFilter in order to support a procedural API
38832
itk::simple::RealToHalfHermitianForwardFFTImageFilter for the object oriented interface
38837
%feature("docstring") itk::simple::ReconstructionByDilation "
38839
grayscale reconstruction by dilation of an image
38842
This function directly calls the execute method of ReconstructionByDilationImageFilter in order to support a procedural API
38846
itk::simple::ReconstructionByDilationImageFilter for the object oriented interface
38851
%feature("docstring") itk::simple::ReconstructionByErosion "
38853
grayscale reconstruction by erosion of an image
38856
This function directly calls the execute method of ReconstructionByErosionImageFilter in order to support a procedural API
38860
itk::simple::ReconstructionByErosionImageFilter for the object oriented interface
38865
%feature("docstring") itk::simple::RecursiveGaussian "
38867
Base class for computing IIR convolution with an approximation of a
38871
This function directly calls the execute method of RecursiveGaussianImageFilter in order to support a procedural API
38875
itk::simple::RecursiveGaussianImageFilter for the object oriented interface
38880
%feature("docstring") itk::simple::RegionalMaxima "
38882
Produce a binary image where foreground is the regional maxima of the
38886
This function directly calls the execute method of RegionalMaximaImageFilter in order to support a procedural API
38890
itk::simple::RegionalMaximaImageFilter for the object oriented interface
38895
%feature("docstring") itk::simple::RegionalMinima "
38897
Produce a binary image where foreground is the regional minima of the
38901
This function directly calls the execute method of RegionalMinimaImageFilter in order to support a procedural API
38905
itk::simple::RegionalMinimaImageFilter for the object oriented interface
38910
%feature("docstring") itk::simple::RegionOfInterest "
38912
Extract a region of interest from the input image.
38915
This function directly calls the execute method of RegionOfInterestImageFilter in order to support a procedural API
38919
itk::simple::RegionOfInterestImageFilter for the object oriented interface
38924
%feature("docstring") itk::simple::RelabelComponent "
38926
Relabel the components in an image such that consecutive labels are
38930
This function directly calls the execute method of RelabelComponentImageFilter in order to support a procedural API
38934
itk::simple::RelabelComponentImageFilter for the object oriented interface
38939
%feature("docstring") itk::simple::RelabelLabelMap "
38941
This filter relabels the LabelObjects; the new labels are arranged
38942
consecutively with consideration for the background value.
38945
This function directly calls the execute method of RelabelLabelMapFilter in order to support a procedural API
38949
itk::simple::RelabelLabelMapFilter for the object oriented interface
38954
%feature("docstring") itk::simple::RenyiEntropyThreshold "
38956
Threshold an image using the RenyiEntropy Threshold.
38959
This function directly calls the execute method of RenyiEntropyThresholdImageFilter in order to support a procedural API
38963
itk::simple::RenyiEntropyThresholdImageFilter for the object oriented interface
38968
%feature("docstring") itk::simple::RenyiEntropyThreshold "
38971
%feature("docstring") itk::simple::RescaleIntensity "
38973
Applies a linear transformation to the intensity levels of the input Image .
38976
This function directly calls the execute method of RescaleIntensityImageFilter in order to support a procedural API
38980
itk::simple::RescaleIntensityImageFilter for the object oriented interface
38985
%feature("docstring") itk::simple::RichardsonLucyDeconvolution "
38987
Deconvolve an image using the Richardson-Lucy deconvolution algorithm.
38990
This function directly calls the execute method of RichardsonLucyDeconvolutionImageFilter in order to support a procedural API
38994
itk::simple::RichardsonLucyDeconvolutionImageFilter for the object oriented interface
38999
%feature("docstring") itk::simple::SaltAndPepperNoise "
39001
Alter an image with fixed value impulse noise, often called salt and
39005
This function directly calls the execute method of SaltAndPepperNoiseImageFilter in order to support a procedural API
39009
itk::simple::SaltAndPepperNoiseImageFilter for the object oriented interface
39014
%feature("docstring") itk::simple::ScalarChanAndVeseDenseLevelSet "
39016
Dense implementation of the Chan and Vese multiphase level set image
39020
This function directly calls the execute method of ScalarChanAndVeseDenseLevelSetImageFilter in order to support a procedural API
39024
itk::simple::ScalarChanAndVeseDenseLevelSetImageFilter for the object oriented interface
39029
%feature("docstring") itk::simple::ScalarConnectedComponent "
39031
A connected components filter that labels the objects in an arbitrary
39032
image. Two pixels are similar if they are within threshold of each
39033
other. Uses ConnectedComponentFunctorImageFilter .
39036
This function directly calls the execute method of ScalarConnectedComponentImageFilter in order to support a procedural API
39040
itk::simple::ScalarConnectedComponentImageFilter for the object oriented interface
39045
%feature("docstring") itk::simple::ScalarImageKmeans "
39047
Classifies the intensity values of a scalar image using the K-Means
39051
This function directly calls the execute method of ScalarImageKmeansImageFilter in order to support a procedural API
39055
itk::simple::ScalarImageKmeansImageFilter for the object oriented interface
39060
%feature("docstring") itk::simple::ScalarToRGBColormap "
39062
Implements pixel-wise intensity->rgb mapping operation on one image.
39065
This function directly calls the execute method of ScalarToRGBColormapImageFilter in order to support a procedural API
39069
itk::simple::ScalarToRGBColormapImageFilter for the object oriented interface
39074
%feature("docstring") itk::simple::ShanbhagThreshold "
39076
Threshold an image using the Shanbhag Threshold.
39079
This function directly calls the execute method of ShanbhagThresholdImageFilter in order to support a procedural API
39083
itk::simple::ShanbhagThresholdImageFilter for the object oriented interface
39088
%feature("docstring") itk::simple::ShanbhagThreshold "
39091
%feature("docstring") itk::simple::ShapeDetectionLevelSet "
39093
Segments structures in images based on a user supplied edge potential
39097
This function directly calls the execute method of ShapeDetectionLevelSetImageFilter in order to support a procedural API
39101
itk::simple::ShapeDetectionLevelSetImageFilter for the object oriented interface
39106
%feature("docstring") itk::simple::ShiftScale "
39108
Shift and scale the pixels in an image.
39111
This function directly calls the execute method of ShiftScaleImageFilter in order to support a procedural API
39115
itk::simple::ShiftScaleImageFilter for the object oriented interface
39120
%feature("docstring") itk::simple::ShotNoise "
39122
Alter an image with shot noise.
39125
This function directly calls the execute method of ShotNoiseImageFilter in order to support a procedural API
39129
itk::simple::ShotNoiseImageFilter for the object oriented interface
39134
%feature("docstring") itk::simple::Show "
39136
Display an image using Fiji, ImageJ or another application.
39138
This function requires that Fiji ( https://fiji.sc ) or ImageJ ( http://rsb.info.nih.gov/ij/) be properly installed for Mac and Windows, and in the user's path
39139
for Linux. ImageJ must have a plugin for reading Nifti formatted files
39140
( http://www.loci.wisc.edu/bio-formats/imagej).
39142
Nifti is the default file format used to export images. A different
39143
format can be chosen by setting the SITK_SHOW_EXTENSION environment
39144
variable. For example, set SITK_SHOW_EXTENSION to \".png\" to use PNG
39147
The user can specify an application other than ImageJ to view images
39148
via the SITK_SHOW_COMMAND environment variable.
39150
The user can also select applications specifically for color images or
39151
3D images using the SITK_SHOW_COLOR_COMMAND and SITK_SHOW_3D_COMMAND
39152
environment variables.
39154
SITK_SHOW_COMMAND, SITK_SHOW_COLOR_COMMAND and SITK_SHOW_3D_COMMAND
39155
allow the following tokens in their strings.\\\\li \\\\c \"%a\" for the ImageJ application \\\\li \\\\c \"%f\"
39156
for SimpleITK's temporary image file
39158
For example, the default SITK_SHOW_COMMAND string on Linux systems is:
39161
After token substitution it may become:
39164
For another example, the default SITK_SHOW_COLOR_COMMAND string on Mac
39168
After token substitution the string may become:
39171
The string after \"-eval\" is an ImageJ macro the opens the file and runs ImageJ's Make
39172
Composite command to display the image in color.
39174
If the \"%f\" token is not found in the command string, the temporary file name is
39175
automatically appended to the command argument list.
39177
When invoked, Show searches for Fiji first, and then ImageJ. Fiji is
39178
the most update-to-date version of ImageJ and includes a lot of
39179
plugins which facilitate scientific image analysis. By default, for a
39180
64-bit build of SimpleITK on Macs, sitkShow searches for ImageJ64.app.
39181
For a 32-bit Mac build, sitkShow searches for ImageJ.app. If the user
39182
prefers a different version of ImageJ (or a different image viewer
39183
altogether), it can be specified using the SITK_SHOW_COMMAND
39184
environment variable.
39186
The boolean parameter debugOn prints the search path Show uses to find
39187
ImageJ, the full path to the ImageJ it found, and the full command
39188
line used to invoke ImageJ.
39192
%feature("docstring") itk::simple::Shrink "
39194
Reduce the size of an image by an integer factor in each dimension.
39197
This function directly calls the execute method of ShrinkImageFilter in order to support a procedural API
39201
itk::simple::ShrinkImageFilter for the object oriented interface
39206
%feature("docstring") itk::simple::Sigmoid "
39208
Computes the sigmoid function pixel-wise.
39211
This function directly calls the execute method of SigmoidImageFilter in order to support a procedural API
39215
itk::simple::SigmoidImageFilter for the object oriented interface
39220
%feature("docstring") itk::simple::SignedDanielssonDistanceMap "
39222
itk::simple::SignedDanielssonDistanceMapImageFilter Procedural Interface
39225
This function directly calls the execute method of SignedDanielssonDistanceMapImageFilter in order to support a procedural API
39229
itk::simple::SignedDanielssonDistanceMapImageFilter for the object oriented interface
39234
%feature("docstring") itk::simple::SignedMaurerDistanceMap "
39236
This filter calculates the Euclidean distance transform of a binary
39237
image in linear time for arbitrary dimensions.
39240
This function directly calls the execute method of SignedMaurerDistanceMapImageFilter in order to support a procedural API
39244
itk::simple::SignedMaurerDistanceMapImageFilter for the object oriented interface
39249
%feature("docstring") itk::simple::SimpleContourExtractor "
39251
Computes an image of contours which will be the contour of the first
39255
This function directly calls the execute method of SimpleContourExtractorImageFilter in order to support a procedural API
39259
itk::simple::SimpleContourExtractorImageFilter for the object oriented interface
39264
%feature("docstring") itk::simple::Sin "
39266
Computes the sine of each pixel.
39269
This function directly calls the execute method of SinImageFilter in order to support a procedural API
39273
itk::simple::SinImageFilter for the object oriented interface
39278
%feature("docstring") itk::simple::sitkITKDirectionToSTL "
39281
%feature("docstring") itk::simple::sitkITKImageRegionToSTL "
39283
Convert an ITK ImageRegion to and std::vector with the first part being the start index followed
39288
%feature("docstring") itk::simple::sitkITKVectorToSTL "
39290
Convert an ITK fixed width vector to a std::vector.
39294
%feature("docstring") itk::simple::sitkITKVectorToSTL "
39297
%feature("docstring") itk::simple::sitkSTLToITKDirection "
39300
%feature("docstring") itk::simple::sitkSTLVectorToITK "
39302
Copy the elements of an std::vector into an ITK fixed width vector.
39305
If there are more elements in paramter \"in\" than the templated ITK
39306
vector type, they are truncated. If less, then an exception is
39311
%feature("docstring") itk::simple::sitkSTLVectorToITKPointVector "
39314
%feature("docstring") itk::simple::Slice "
39316
itk::simple::SliceImageFilter Procedural Interface
39319
This function directly calls the execute method of SliceImageFilter in order to support a procedural API
39323
itk::simple::SliceImageFilter for the object oriented interface
39328
%feature("docstring") itk::simple::SmoothingRecursiveGaussian "
39330
Computes the smoothing of an image by convolution with the Gaussian
39331
kernels implemented as IIR filters.
39334
This function directly calls the execute method of SmoothingRecursiveGaussianImageFilter in order to support a procedural API
39338
itk::simple::SmoothingRecursiveGaussianImageFilter for the object oriented interface
39343
%feature("docstring") itk::simple::SobelEdgeDetection "
39345
A 2D or 3D edge detection using the Sobel operator.
39348
This function directly calls the execute method of SobelEdgeDetectionImageFilter in order to support a procedural API
39352
itk::simple::SobelEdgeDetectionImageFilter for the object oriented interface
39357
%feature("docstring") itk::simple::SpeckleNoise "
39359
Alter an image with speckle (multiplicative) noise.
39362
This function directly calls the execute method of SpeckleNoiseImageFilter in order to support a procedural API
39366
itk::simple::SpeckleNoiseImageFilter for the object oriented interface
39371
%feature("docstring") itk::simple::Sqrt "
39373
Computes the square root of each pixel.
39376
This function directly calls the execute method of SqrtImageFilter in order to support a procedural API
39380
itk::simple::SqrtImageFilter for the object oriented interface
39385
%feature("docstring") itk::simple::Square "
39387
Computes the square of the intensity values pixel-wise.
39390
This function directly calls the execute method of SquareImageFilter in order to support a procedural API
39394
itk::simple::SquareImageFilter for the object oriented interface
39399
%feature("docstring") itk::simple::SquaredDifference "
39401
Implements pixel-wise the computation of squared difference.
39404
This function directly calls the execute method of SquaredDifferenceImageFilter in order to support a procedural API
39408
itk::simple::SquaredDifferenceImageFilter for the object oriented interface
39413
%feature("docstring") itk::simple::SquaredDifference "
39416
%feature("docstring") itk::simple::SquaredDifference "
39419
%feature("docstring") itk::simple::StandardDeviationProjection "
39424
This function directly calls the execute method of StandardDeviationProjectionImageFilter in order to support a procedural API
39428
itk::simple::StandardDeviationProjectionImageFilter for the object oriented interface
39433
%feature("docstring") itk::simple::Subtract "
39435
Pixel-wise subtraction of two images.
39438
This function directly calls the execute method of SubtractImageFilter in order to support a procedural API
39442
itk::simple::SubtractImageFilter for the object oriented interface
39447
%feature("docstring") itk::simple::Subtract "
39450
%feature("docstring") itk::simple::Subtract "
39453
%feature("docstring") itk::simple::SumProjection "
39458
This function directly calls the execute method of SumProjectionImageFilter in order to support a procedural API
39462
itk::simple::SumProjectionImageFilter for the object oriented interface
39467
%feature("docstring") itk::simple::Tan "
39469
Computes the tangent of each input pixel.
39472
This function directly calls the execute method of TanImageFilter in order to support a procedural API
39476
itk::simple::TanImageFilter for the object oriented interface
39481
%feature("docstring") itk::simple::TernaryAdd "
39483
Pixel-wise addition of three images.
39486
This function directly calls the execute method of TernaryAddImageFilter in order to support a procedural API
39490
itk::simple::TernaryAddImageFilter for the object oriented interface
39495
%feature("docstring") itk::simple::TernaryMagnitude "
39497
Compute the pixel-wise magnitude of three images.
39500
This function directly calls the execute method of TernaryMagnitudeImageFilter in order to support a procedural API
39504
itk::simple::TernaryMagnitudeImageFilter for the object oriented interface
39509
%feature("docstring") itk::simple::TernaryMagnitudeSquared "
39511
Compute the pixel-wise squared magnitude of three images.
39514
This function directly calls the execute method of TernaryMagnitudeSquaredImageFilter in order to support a procedural API
39518
itk::simple::TernaryMagnitudeSquaredImageFilter for the object oriented interface
39523
%feature("docstring") itk::simple::Threshold "
39525
Set image values to a user-specified value if they are below, above,
39526
or between simple threshold values.
39529
This function directly calls the execute method of ThresholdImageFilter in order to support a procedural API
39533
itk::simple::ThresholdImageFilter for the object oriented interface
39538
%feature("docstring") itk::simple::ThresholdMaximumConnectedComponents "
39540
Finds the threshold value of an image based on maximizing the number
39541
of objects in the image that are larger than a given minimal size.
39544
This function directly calls the execute method of ThresholdMaximumConnectedComponentsImageFilter in order to support a procedural API
39548
itk::simple::ThresholdMaximumConnectedComponentsImageFilter for the object oriented interface
39553
%feature("docstring") itk::simple::ThresholdSegmentationLevelSet "
39555
Segments structures in images based on intensity values.
39558
This function directly calls the execute method of ThresholdSegmentationLevelSetImageFilter in order to support a procedural API
39562
itk::simple::ThresholdSegmentationLevelSetImageFilter for the object oriented interface
39567
%feature("docstring") itk::simple::TikhonovDeconvolution "
39569
An inverse deconvolution filter regularized in the Tikhonov sense.
39572
This function directly calls the execute method of TikhonovDeconvolutionImageFilter in order to support a procedural API
39576
itk::simple::TikhonovDeconvolutionImageFilter for the object oriented interface
39581
%feature("docstring") itk::simple::TransformToDisplacementField "
39583
Generate a displacement field from a coordinate transform.
39586
This function directly calls the execute method of TransformToDisplacementFieldFilter in order to support a procedural API
39590
itk::simple::TransformToDisplacementFieldFilter for the object oriented interface
39595
%feature("docstring") itk::simple::TriangleThreshold "
39597
Threshold an image using the Triangle Threshold.
39600
This function directly calls the execute method of TriangleThresholdImageFilter in order to support a procedural API
39604
itk::simple::TriangleThresholdImageFilter for the object oriented interface
39609
%feature("docstring") itk::simple::TriangleThreshold "
39612
%feature("docstring") itk::simple::UnaryMinus "
39614
Computes the negative of each pixel.
39617
This function directly calls the execute method of UnaryMinusImageFilter in order to support a procedural API
39621
itk::simple::UnaryMinusImageFilter for the object oriented interface
39626
%feature("docstring") itk::simple::Unused "
39628
A function which does nothing.
39631
This function is to be used to mark parameters as unused to supress
39636
%feature("docstring") itk::simple::ValuedRegionalMaxima "
39638
Transforms the image so that any pixel that is not a regional maxima
39639
is set to the minimum value for the pixel type. Pixels that are
39640
regional maxima retain their value.
39643
This function directly calls the execute method of ValuedRegionalMaximaImageFilter in order to support a procedural API
39647
itk::simple::ValuedRegionalMaximaImageFilter for the object oriented interface
39652
%feature("docstring") itk::simple::ValuedRegionalMinima "
39654
Transforms the image so that any pixel that is not a regional minima
39655
is set to the maximum value for the pixel type. Pixels that are
39656
regional minima retain their value.
39659
This function directly calls the execute method of ValuedRegionalMinimaImageFilter in order to support a procedural API
39663
itk::simple::ValuedRegionalMinimaImageFilter for the object oriented interface
39668
%feature("docstring") itk::simple::VectorConfidenceConnected "
39670
itk::simple::VectorConfidenceConnectedImageFilter Functional Interface
39672
This function directly calls the execute method of VectorConfidenceConnectedImageFilter in order to support a fully functional API
39676
%feature("docstring") itk::simple::VectorConnectedComponent "
39678
A connected components filter that labels the objects in a vector
39679
image. Two vectors are pointing similar directions if one minus their
39680
dot product is less than a threshold. Vectors that are 180 degrees out
39681
of phase are similar. Assumes that vectors are normalized.
39684
This function directly calls the execute method of VectorConnectedComponentImageFilter in order to support a procedural API
39688
itk::simple::VectorConnectedComponentImageFilter for the object oriented interface
39693
%feature("docstring") itk::simple::VectorIndexSelectionCast "
39695
Extracts the selected index of the vector that is the input pixel
39699
This function directly calls the execute method of VectorIndexSelectionCastImageFilter in order to support a procedural API
39703
itk::simple::VectorIndexSelectionCastImageFilter for the object oriented interface
39708
%feature("docstring") itk::simple::VectorMagnitude "
39710
Take an image of vectors as input and produce an image with the
39711
magnitude of those vectors.
39714
This function directly calls the execute method of VectorMagnitudeImageFilter in order to support a procedural API
39718
itk::simple::VectorMagnitudeImageFilter for the object oriented interface
39723
%feature("docstring") itk::simple::VotingBinary "
39725
Applies a voting operation in a neighborhood of each pixel.
39728
This function directly calls the execute method of VotingBinaryImageFilter in order to support a procedural API
39732
itk::simple::VotingBinaryImageFilter for the object oriented interface
39737
%feature("docstring") itk::simple::VotingBinaryHoleFilling "
39739
Fills in holes and cavities by applying a voting operation on each
39743
This function directly calls the execute method of VotingBinaryHoleFillingImageFilter in order to support a procedural API
39747
itk::simple::VotingBinaryHoleFillingImageFilter for the object oriented interface
39752
%feature("docstring") itk::simple::VotingBinaryIterativeHoleFilling "
39754
Fills in holes and cavities by iteratively applying a voting
39758
This function directly calls the execute method of VotingBinaryIterativeHoleFillingImageFilter in order to support a procedural API
39762
itk::simple::VotingBinaryIterativeHoleFillingImageFilter for the object oriented interface
39767
%feature("docstring") itk::simple::Warp "
39769
Warps an image using an input displacement field.
39772
This function directly calls the execute method of WarpImageFilter in order to support a procedural API
39776
itk::simple::WarpImageFilter for the object oriented interface
39781
%feature("docstring") itk::simple::WhiteTopHat "
39783
itk::simple::WhiteTopHatImageFilter Functional Interface
39785
This function directly calls the execute method of WhiteTopHatImageFilter in order to support a fully functional API
39789
%feature("docstring") itk::simple::WhiteTopHat "
39791
itk::simple::WhiteTopHatImageFilter Functional Interface
39793
This function directly calls the execute method of WhiteTopHatImageFilter in order to support a fully functional API
39797
%feature("docstring") itk::simple::WienerDeconvolution "
39799
The Wiener deconvolution image filter is designed to restore an image
39800
convolved with a blurring kernel while keeping noise enhancement to a
39804
This function directly calls the execute method of WienerDeconvolutionImageFilter in order to support a procedural API
39808
itk::simple::WienerDeconvolutionImageFilter for the object oriented interface
39813
%feature("docstring") itk::simple::WrapPad "
39815
Increase the image size by padding with replicants of the input image
39819
This function directly calls the execute method of WrapPadImageFilter in order to support a procedural API
39823
itk::simple::WrapPadImageFilter for the object oriented interface
39828
%feature("docstring") itk::simple::WriteImage "
39831
%feature("docstring") itk::simple::WriteImage "
39834
%feature("docstring") itk::simple::WriteTransform "
39837
%feature("docstring") itk::simple::Xor "
39839
Computes the XOR bitwise operator pixel-wise between two images.
39842
This function directly calls the execute method of XorImageFilter in order to support a procedural API
39846
itk::simple::XorImageFilter for the object oriented interface
39851
%feature("docstring") itk::simple::Xor "
39854
%feature("docstring") itk::simple::Xor "
39857
%feature("docstring") itk::simple::YenThreshold "
39859
Threshold an image using the Yen Threshold.
39862
This function directly calls the execute method of YenThresholdImageFilter in order to support a procedural API
39866
itk::simple::YenThresholdImageFilter for the object oriented interface
39871
%feature("docstring") itk::simple::YenThreshold "
39874
%feature("docstring") itk::simple::ZeroCrossing "
39876
This filter finds the closest pixel to the zero-crossings (sign
39877
changes) in a signed itk::Image .
39880
This function directly calls the execute method of ZeroCrossingImageFilter in order to support a procedural API
39884
itk::simple::ZeroCrossingImageFilter for the object oriented interface
39889
%feature("docstring") itk::simple::ZeroCrossingBasedEdgeDetection "
39891
This filter implements a zero-crossing based edge detecor.
39894
This function directly calls the execute method of ZeroCrossingBasedEdgeDetectionImageFilter in order to support a procedural API
39898
itk::simple::ZeroCrossingBasedEdgeDetectionImageFilter for the object oriented interface
39903
%feature("docstring") itk::simple::ZeroFluxNeumannPad "
39905
Increase the image size by padding according to the zero-flux Neumann
39906
boundary condition.
39909
This function directly calls the execute method of ZeroFluxNeumannPadImageFilter in order to support a procedural API
39913
itk::simple::ZeroFluxNeumannPadImageFilter for the object oriented interface
39919
%feature("docstring") itk::simple::BasicPixelID "
39921
This type is used as an identity for pixel of itk::Image type
39923
This is an empty type which is used for compile-time meta-programming.
39924
It does not contain any information, an image type can be converted to
39925
one of the PixelID types, and an PixelID can be converted to a value.
39926
However, a run-time value can not be converted to this compile time
39935
ImageTypeToPixelIDValue
39937
PixelIDToPixelIDValue
39940
C++ includes: sitkPixelIDTypes.h
39944
%feature("docstring") itk::simple::Conditional "
39945
C++ includes: sitkConditional.h
39949
%feature("docstring") itk::simple::ConditionalValue "
39950
C++ includes: sitkConditional.h
39954
%feature("docstring") itk::simple::DisableIf "
39955
C++ includes: sitkEnableIf.h
39959
%feature("docstring") itk::simple::EnableIf "
39960
C++ includes: sitkEnableIf.h
39964
%feature("docstring") itk::simple::ImageTypeToPixelID "
39966
A meta-programming tool to query the PixelID property of an \"itk
39967
image type\" at compile type
39969
This structure contains one property,
39970
ImageTypeToPixelID<T>::PixelIDType is the \"itk image type\" of the
39981
ImageTypeToPixelIDValue
39984
C++ includes: sitkPixelIDTypes.h
39988
%feature("docstring") itk::simple::ImageTypeToPixelIDValue "
39989
C++ includes: sitkPixelIDValues.h
39993
%feature("docstring") itk::simple::ImageTypeToPixelID< itk::Image< TPixelType, VImageDimension > > "
39994
C++ includes: sitkPixelIDTypes.h
39998
%feature("docstring") itk::simple::ImageTypeToPixelID< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > > > "
39999
C++ includes: sitkPixelIDTypes.h
40003
%feature("docstring") itk::simple::ImageTypeToPixelID< itk::VectorImage< TPixelType, VImageDimension > > "
40004
C++ includes: sitkPixelIDTypes.h
40008
%feature("docstring") itk::simple::IsBasic "
40009
C++ includes: sitkPixelIDTokens.h
40013
%feature("docstring") itk::simple::IsBasic< BasicPixelID< TPixelType > > "
40014
C++ includes: sitkPixelIDTokens.h
40018
%feature("docstring") itk::simple::IsBasic< itk::Image< TPixelType, VImageDimension > > "
40019
C++ includes: sitkPixelIDTokens.h
40023
%feature("docstring") itk::simple::IsInstantiated "
40024
C++ includes: sitkPixelIDTokens.h
40028
%feature("docstring") itk::simple::IsInstantiated< itk::Image< TPixelType, VImageDimension >, 0 > "
40029
C++ includes: sitkPixelIDTokens.h
40033
%feature("docstring") itk::simple::IsInstantiated< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > >, 0 > "
40034
C++ includes: sitkPixelIDTokens.h
40038
%feature("docstring") itk::simple::IsInstantiated< itk::VectorImage< TPixelType, VImageDimension >, 0 > "
40039
C++ includes: sitkPixelIDTokens.h
40043
%feature("docstring") itk::simple::IsLabel "
40044
C++ includes: sitkPixelIDTokens.h
40048
%feature("docstring") itk::simple::IsLabel< LabelPixelID< TPixelType > > "
40049
C++ includes: sitkPixelIDTokens.h
40053
%feature("docstring") itk::simple::IsLabel< itk::LabelMap< itk::LabelObject< TLabelType, VImageDimension > > > "
40054
C++ includes: sitkPixelIDTokens.h
40058
%feature("docstring") itk::simple::IsVector "
40059
C++ includes: sitkPixelIDTokens.h
40063
%feature("docstring") itk::simple::IsVector< VectorPixelID< TPixelType > > "
40064
C++ includes: sitkPixelIDTokens.h
40068
%feature("docstring") itk::simple::IsVector< itk::VectorImage< TPixelType, VImageDimension > > "
40069
C++ includes: sitkPixelIDTokens.h
40073
%feature("docstring") itk::simple::LabelPixelID "
40075
This type is used as an identity for pixel of itk::LabelMap type
40077
This is an empty type which is used for compile-time meta-programming.
40078
It does not contain any information, an image type can be converted to
40079
one of the PixelID types, and an PixelID can be converted to a value.
40080
However, a run-time value can not be converted to this compile time
40089
ImageTypeToPixelIDValue
40091
PixelIDToPixelIDValue
40094
C++ includes: sitkPixelIDTypes.h
40098
%feature("docstring") itk::simple::PixelIDToImageType "
40100
A meta-programming tool to query the \"itk image type\" if a PixelID
40103
This structure contains one property, PixelIDToImageType<T>::ImageType
40104
is the \"itk image type\" of the pixel ID.
40114
ImageTypeToPixelIDValue
40117
C++ includes: sitkPixelIDTypes.h
40121
%feature("docstring") itk::simple::PixelIDToImageType< BasicPixelID< TPixelType >, VImageDimension > "
40122
C++ includes: sitkPixelIDTypes.h
40126
%feature("docstring") itk::simple::PixelIDToImageType< LabelPixelID< TLabelType >, VImageDimension > "
40127
C++ includes: sitkPixelIDTypes.h
40131
%feature("docstring") itk::simple::PixelIDToImageType< VectorPixelID< TVectorPixelType >, VImageDimension > "
40132
C++ includes: sitkPixelIDTypes.h
40136
%feature("docstring") itk::simple::PixelIDToPixelIDValue "
40137
C++ includes: sitkPixelIDValues.h
40141
%feature("docstring") itk::simple::StaticAssertFailure "
40142
C++ includes: sitkMacro.h
40146
%feature("docstring") itk::simple::StaticAssertFailure< true > "
40147
C++ includes: sitkMacro.h
40151
%feature("docstring") itk::simple::VectorPixelID "
40153
This type is used as an identity for pixel of itk::VectorImage type
40155
This is an empty type which is used for compile-time meta-programming.
40156
It does not contain any information, an image type can be converted to
40157
one of the PixelID types, and an PixelID can be converted to a value.
40158
However, a run-time value can not be converted to this compile time
40167
ImageTypeToPixelIDValue
40169
PixelIDToPixelIDValue
40172
C++ includes: sitkPixelIDTypes.h
40176
%feature("docstring") itk::simple::DualExecuteInternalAddressor "
40177
C++ includes: sitkDetail.h
40181
%feature("docstring") itk::simple::DualExecuteInternalVectorAddressor "
40183
An addressor of ExecuteInternalCast to be utilized with registering
40184
member functions with the factory.
40186
C++ includes: sitkDetail.h
40190
%feature("docstring") itk::simple::ExecuteInternalLabelImageAddressor "
40192
An addressor of ExecuteInternal to be utilized with registering member
40193
functions with the factory.
40195
C++ includes: sitkDetail.h
40199
%feature("docstring") itk::simple::ExecuteInternalVectorImageAddressor "
40201
An addressor of ExecuteInternalCast to be utilized with registering
40202
member functions with the factory.
40204
C++ includes: sitkDetail.h
40208
%feature("docstring") itk::simple::MemberFunctionAddressor "
40209
C++ includes: sitkDetail.h