TubeTK/Documentation/SegmentConnectedComponentsUsingParzenPDFs
From KitwarePublic
< TubeTK | Documentation
Jump to navigationJump to search
Description: Given multiple, registered images and foreground and background masks, computes multivariate PDFs for inside and outside classes, and then performs competitive region growing.
USAGE:
./SegmentConnectedComponentsUsingParzenPDFs [--returnparameterfile <std::string>] [--processinformationaddress <std::string>] [--xml] [--echo] [--saveClassPDFBase <std::string>] [--loadClassPDFBase <std::string>] [--saveClassProbabilityVolumeBase <std::string>] [--forceClassification] [--reclassifyNotObjectLabels] [--reclassifyObjectLabels] [--draft] [--histogramSmoothingStdDev <double>] [--probImageSmoothingStdDev <double>] [--objectPDFWeight <std::vector<double>>] [--dilateFirst] [--holeFillIterations <int>] [--erodeRadius <int>] [--voidId <int>] [--objectId <std::vector<int>>] [--inputVolume4 <std::string>] [--inputVolume3 <std::string>] [--inputVolume2 <std::string>] [--] [--version] [-h] <std::string> <std::string> <std::string>
Where:
--returnparameterfile <std::string> Filename in which to write simple return parameters (int, float, int-vector, etc.) as opposed to bulk return parameters (image, geometry, transform, measurement, table).
--processinformationaddress <std::string> Address of a structure to store process information (progress, abort, etc.). (default: 0)
--xml Produce xml description of command line arguments (default: 0)
--echo Echo the command line arguments (default: 0)
--saveClassPDFBase <std::string> Save images that represent probability density functions.
--loadClassPDFBase <std::string> Load images that represent probability density functions.
--saveClassProbabilityVolumeBase <std::string> Save images where each represents the probability of being a particular object at each voxel. Image files create = base.classNum.mha.
--forceClassification Force classification using simple maximum likelihood. (default: 0)
--reclassifyNotObjectLabels Perform classification on all non-void voxels. (default: 0)
--reclassifyObjectLabels Perform classification on voxels within the object mask. (default: 0)
--draft Generate draft results. (default: 0)
--histogramSmoothingStdDev <double> Standard deviation of blur applied to convert the histogram to a probability density function estimate (default: 5)
--probImageSmoothingStdDev <double> Standard deviation of blur applied to probability images prior to computing maximum likelihood of each class at each pixel (default: 1)
--objectPDFWeight <std::vector<double>> Relative weight (multiplier) of each PDF. (default: 1)
--dilateFirst Performs dilation then erosion (versus opposite order) to help fill-in sparse models. (default: 0)
--holeFillIterations <int> Number of iterations for hole filling. (default: 1)
--erodeRadius <int> Radius of noise to clip from edges. (default: 1)
--voidId <int> Value that represents 'nothing' in the label map. (default: 0)
--objectId <std::vector<int>> List of values that represent the objects in the label map. (default: 255,127)
--inputVolume4 <std::string> Input volume 4.
--inputVolume3 <std::string> Input volume 3.
--inputVolume2 <std::string> Input volume 2.
--, --ignore_rest Ignores the rest of the labeled arguments following this flag.
--version Displays version information and exits.
-h, --help Displays usage information and exits.
<std::string> (required) Input volume 1.
<std::string> (required) Label map that designates the object of interest and 'other.'
<std::string> (required) Segmentation results.
Author(s): Stephen R. Aylward (Kitware)
Acknowledgements: This work is part of the TubeTK project at Kitware.