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# interfaces.slicer.segmentation.specialized

## BRAINSROIAuto

Link to code

Wraps command **BRAINSROIAuto **

title: Foreground masking (BRAINS)

category: Segmentation.Specialized

description: This tool uses a combination of otsu thresholding and a closing operations to identify the most prominant foreground region in an image.

version: 2.4.1

license: https://www.nitrc.org/svn/brains/BuildScripts/trunk/License.txt

contributor: Hans J. Johnson, hans-johnson -at- uiowa.edu, http://wwww.psychiatry.uiowa.edu

acknowledgements: Hans Johnson(1,3,4); Kent Williams(1); Gregory Harris(1), Vincent Magnotta(1,2,3); Andriy Fedorov(5), fedorov -at- bwh.harvard.edu (Slicer integration); (1=University of Iowa Department of Psychiatry, 2=University of Iowa Department of Radiology, 3=University of Iowa Department of Biomedical Engineering, 4=University of Iowa Department of Electrical and Computer Engineering, 5=Surgical Planning Lab, Harvard)

Inputs:

    [Mandatory]
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output

    [Optional]
    ROIAutoDilateSize: (a float)
            This flag is only relavent when using ROIAUTO mode for initializing masks.  It defines
            the final dilation size to capture a bit of background outside the tissue region.  At
            setting of 10mm has been shown to help regularize a BSpline registration type so that
            there is some background constraints to match the edges of the head better.
    args: (a string)
            Additional parameters to the command
    closingSize: (a float)
            The Closing Size (in millimeters) for largest connected filled mask.  This value is
            divided by image spacing and rounded to the next largest voxel number.
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    inputVolume: (an existing file name)
            The input image for finding the largest region filled mask.
    numberOfThreads: (an integer)
            Explicitly specify the maximum number of threads to use.
    otsuPercentileThreshold: (a float)
            Parameter to the Otsu threshold algorithm.
    outputClippedVolumeROI: (a boolean or a file name)
            The inputVolume clipped to the region of the brain mask.
    outputROIMaskVolume: (a boolean or a file name)
            The ROI automatically found from the input image.
    outputVolumePixelType: ('float' or 'short' or 'ushort' or 'int' or 'uint' or 'uchar')
            The output image Pixel Type is the scalar datatype for representation of the Output
            Volume.
    thresholdCorrectionFactor: (a float)
            A factor to scale the Otsu algorithm's result threshold, in case clipping mangles the
            image.

Outputs:

    outputClippedVolumeROI: (an existing file name)
            The inputVolume clipped to the region of the brain mask.
    outputROIMaskVolume: (an existing file name)
            The ROI automatically found from the input image.

## EMSegmentCommandLine

Link to code

Wraps command **EMSegmentCommandLine **

title:
  EMSegment Command-line
category:
  Segmentation.Specialized
description:
  This module is used to simplify the process of segmenting large collections of images by providing a command line interface to the EMSegment algorithm for script and batch processing.

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.0/EMSegment_Command-line

contributor: Sebastien Barre, Brad Davis, Kilian Pohl, Polina Golland, Yumin Yuan, Daniel Haehn

acknowledgements: Many people and organizations have contributed to the funding, design, and development of the EMSegment algorithm and its various implementations.

Inputs:

    [Mandatory]
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output

    [Optional]
    args: (a string)
            Additional parameters to the command
    atlasVolumeFileNames: (an existing file name)
            Use an alternative atlas to the one that is specified by the mrml file - note the order
            matters !
    disableCompression: (a boolean)
            Don't use compression when writing result image to disk.
    disableMultithreading: (an integer)
            Disable multithreading for the EMSegmenter algorithm only! Preprocessing might still run
            in multi-threaded mode. -1: Do not overwrite default value. 0: Disable. 1: Enable.
    dontUpdateIntermediateData: (an integer)
            Disable update of intermediate results.  -1: Do not overwrite default value. 0: Disable.
            1: Enable.
    dontWriteResults: (a boolean)
            Used for testing.  Don't actually write the resulting labelmap to disk.
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    generateEmptyMRMLSceneAndQuit: (a boolean or a file name)
            Used for testing.  Only write a scene with default mrml parameters.
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    intermediateResultsDirectory: (an existing directory name)
            Directory where EMSegmenter will write intermediate data (e.g., aligned atlas data).
    keepTempFiles: (a boolean)
            If flag is set then at the end of command the temporary files are not removed
    loadAtlasNonCentered: (a boolean)
            Read atlas files non-centered.
    loadTargetCentered: (a boolean)
            Read target files centered.
    mrmlSceneFileName: (an existing file name)
            Active MRML scene that contains EMSegment algorithm parameters.
    parametersMRMLNodeName: (a string)
            The name of the EMSegment parameters node within the active MRML scene.  Leave blank for
            default.
    registrationAffineType: (an integer)
            specify the accuracy of the affine registration. -2: Do not overwrite default, -1: Test,
            0: Disable, 1: Fast, 2: Accurate
    registrationDeformableType: (an integer)
            specify the accuracy of the deformable registration. -2: Do not overwrite default, -1:
            Test, 0: Disable, 1: Fast, 2: Accurate
    registrationPackage: (a string)
            specify the registration package for preprocessing (CMTK or BRAINS or PLASTIMATCH or
            DEMONS)
    resultMRMLSceneFileName: (a boolean or a file name)
            Write out the MRML scene after command line substitutions have been made.
    resultStandardVolumeFileName: (an existing file name)
            Used for testing.  Compare segmentation results to this image and return EXIT_FAILURE if
            they do not match.
    resultVolumeFileName: (a boolean or a file name)
            The file name that the segmentation result volume will be written to.
    targetVolumeFileNames: (an existing file name)
            File names of target volumes (to be segmented).  The number of target images must be
            equal to the number of target images specified in the parameter set, and these images
            must be spatially aligned.
    taskPreProcessingSetting: (a string)
            Specifies the different task parameter. Leave blank for default.
    verbose: (a boolean)
            Enable verbose output.

Outputs:

    generateEmptyMRMLSceneAndQuit: (an existing file name)
            Used for testing.  Only write a scene with default mrml parameters.
    resultMRMLSceneFileName: (an existing file name)
            Write out the MRML scene after command line substitutions have been made.
    resultVolumeFileName: (an existing file name)
            The file name that the segmentation result volume will be written to.

## RobustStatisticsSegmenter

Link to code

Wraps command **RobustStatisticsSegmenter **

title: Robust Statistics Segmenter

category: Segmentation.Specialized

description: Active contour segmentation using robust statistic.

version: 1.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/RobustStatisticsSegmenter

contributor: Yi Gao (gatech), Allen Tannenbaum (gatech), Ron Kikinis (SPL, BWH)

acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health

Inputs:

    [Mandatory]
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output

    [Optional]
    args: (a string)
            Additional parameters to the command
    curvatureWeight: (a float)
            Given sphere 1.0 score and extreme rough bounday/surface 0 score, what is the expected
            smoothness of the object?
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    expectedVolume: (a float)
            The approximate volume of the object, in mL.
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    intensityHomogeneity: (a float)
            What is the homogeneity of intensity within the object? Given constant intensity at 1.0
            score and extreme fluctuating intensity at 0.
    labelImageFileName: (an existing file name)
            Label image for initialization
    labelValue: (an integer)
            Label value of the output image
    maxRunningTime: (a float)
            The program will stop if this time is reached.
    originalImageFileName: (an existing file name)
            Original image to be segmented
    segmentedImageFileName: (a boolean or a file name)
            Segmented image

Outputs:

    segmentedImageFileName: (an existing file name)
            Segmented image