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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: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

    [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.
            flag: --ROIAutoDilateSize %f
    args: (a string)
            Additional parameters to the command
            flag: %s
    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.
            flag: --closingSize %f
    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.
            flag: --inputVolume %s
    numberOfThreads: (an integer)
            Explicitly specify the maximum number of threads to use.
            flag: --numberOfThreads %d
    otsuPercentileThreshold: (a float)
            Parameter to the Otsu threshold algorithm.
            flag: --otsuPercentileThreshold %f
    outputClippedVolumeROI: (a boolean or a file name)
            The inputVolume clipped to the region of the brain mask.
            flag: --outputClippedVolumeROI %s
    outputROIMaskVolume: (a boolean or a file name)
            The ROI automatically found from the input image.
            flag: --outputROIMaskVolume %s
    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.
            flag: --outputVolumePixelType %s
    thresholdCorrectionFactor: (a float)
            A factor to scale the Otsu algorithm's result threshold, in case
            clipping mangles the image.
            flag: --thresholdCorrectionFactor %f

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: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    atlasVolumeFileNames: (an existing file name)
            Use an alternative atlas to the one that is specified by the mrml
            file - note the order matters !
            flag: --atlasVolumeFileNames %s...
    disableCompression: (a boolean)
            Don't use compression when writing result image to disk.
            flag: --disableCompression
    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.
            flag: --disableMultithreading %d
    dontUpdateIntermediateData: (an integer)
            Disable update of intermediate results. -1: Do not overwrite default
            value. 0: Disable. 1: Enable.
            flag: --dontUpdateIntermediateData %d
    dontWriteResults: (a boolean)
            Used for testing. Don't actually write the resulting labelmap to
            disk.
            flag: --dontWriteResults
    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.
            flag: --generateEmptyMRMLSceneAndQuit %s
    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).
            flag: --intermediateResultsDirectory %s
    keepTempFiles: (a boolean)
            If flag is set then at the end of command the temporary files are
            not removed
            flag: --keepTempFiles
    loadAtlasNonCentered: (a boolean)
            Read atlas files non-centered.
            flag: --loadAtlasNonCentered
    loadTargetCentered: (a boolean)
            Read target files centered.
            flag: --loadTargetCentered
    mrmlSceneFileName: (an existing file name)
            Active MRML scene that contains EMSegment algorithm parameters.
            flag: --mrmlSceneFileName %s
    parametersMRMLNodeName: (a string)
            The name of the EMSegment parameters node within the active MRML
            scene. Leave blank for default.
            flag: --parametersMRMLNodeName %s
    registrationAffineType: (an integer)
            specify the accuracy of the affine registration. -2: Do not
            overwrite default, -1: Test, 0: Disable, 1: Fast, 2: Accurate
            flag: --registrationAffineType %d
    registrationDeformableType: (an integer)
            specify the accuracy of the deformable registration. -2: Do not
            overwrite default, -1: Test, 0: Disable, 1: Fast, 2: Accurate
            flag: --registrationDeformableType %d
    registrationPackage: (a string)
            specify the registration package for preprocessing (CMTK or BRAINS
            or PLASTIMATCH or DEMONS)
            flag: --registrationPackage %s
    resultMRMLSceneFileName: (a boolean or a file name)
            Write out the MRML scene after command line substitutions have been
            made.
            flag: --resultMRMLSceneFileName %s
    resultStandardVolumeFileName: (an existing file name)
            Used for testing. Compare segmentation results to this image and
            return EXIT_FAILURE if they do not match.
            flag: --resultStandardVolumeFileName %s
    resultVolumeFileName: (a boolean or a file name)
            The file name that the segmentation result volume will be written
            to.
            flag: --resultVolumeFileName %s
    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.
            flag: --targetVolumeFileNames %s...
    taskPreProcessingSetting: (a string)
            Specifies the different task parameter. Leave blank for default.
            flag: --taskPreProcessingSetting %s
    verbose: (a boolean)
            Enable verbose output.
            flag: --verbose

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: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    curvatureWeight: (a float)
            Given sphere 1.0 score and extreme rough bounday/surface 0 score,
            what is the expected smoothness of the object?
            flag: --curvatureWeight %f
    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.
            flag: --expectedVolume %f
    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.
            flag: --intensityHomogeneity %f
    labelImageFileName: (an existing file name)
            Label image for initialization
            flag: %s, position: -2
    labelValue: (an integer)
            Label value of the output image
            flag: --labelValue %d
    maxRunningTime: (a float)
            The program will stop if this time is reached.
            flag: --maxRunningTime %f
    originalImageFileName: (an existing file name)
            Original image to be segmented
            flag: %s, position: -3
    segmentedImageFileName: (a boolean or a file name)
            Segmented image
            flag: %s, position: -1

Outputs:

    segmentedImageFileName: (an existing file name)
            Segmented image