2
"name" : "StatisticsImageFilter",
3
"template_code_filename" : "ImageFilter",
4
"template_test_filename" : "ImageFilter",
5
"number_of_inputs" : 1,
7
"pixel_types" : "BasicPixelIDTypeList",
8
"filter_type" : "itk::StatisticsImageFilter<InputImageType>",
10
"no_return_image" : true,
17
"briefdescriptionGet" : "",
18
"detaileddescriptionGet" : "Return the computed Minimum."
24
"briefdescriptionGet" : "",
25
"detaileddescriptionGet" : "Return the computed Maximum."
31
"briefdescriptionGet" : "",
32
"detaileddescriptionGet" : "Return the computed Mean."
38
"briefdescriptionGet" : "",
39
"detaileddescriptionGet" : "Return the computed Standard Deviation."
45
"briefdescriptionGet" : "",
46
"detaileddescriptionGet" : "Return the computed Variance."
52
"briefdescriptionGet" : "",
53
"detaileddescriptionGet" : "Return the compute Sum."
59
"description" : "statistics on cthead1",
61
"measurements_results" : [
72
"value" : "77.7415618",
82
"value" : "6124.9260064656282",
95
"briefdescription" : "Compute min. max, variance and mean of an Image .",
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"detaileddescription" : "StatisticsImageFilter computes the minimum, maximum, sum, mean, variance sigma of an image. The filter needs all of its input image. It behaves as a filter with an input and output. Thus it can be inserted in a pipline with other filters and the statistics will only be recomputed if a downstream filter changes.\n\nThe filter passes its input through unmodified. The filter is threaded. It computes statistics in each thread then combines them in its AfterThreadedGenerate method.\n\n\\par Wiki Examples:\n\n\\li All Examples \n\n\\li Compute min, max, variance and mean of an Image.",
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"itk_module" : "ITKImageStatistics",
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"itk_group" : "ImageStatistics"
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