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# interfaces.mipav.developer

## JistBrainMgdmSegmentation

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.brain.JistBrainMgdmSegmentation **

title: MGDM Whole Brain Segmentation

category: Developer Tools

description: Estimate brain structures from an atlas for a MRI dataset (multiple input combinations are possible).

version: 2.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inAdjust: ('true' or 'false')
            Adjust intensity priors
            flag: --inAdjust %s
    inAtlas: (an existing file name)
            Atlas file
            flag: --inAtlas %s
    inCompute: ('true' or 'false')
            Compute posteriors
            flag: --inCompute %s
    inCurvature: (a float)
            Curvature weight
            flag: --inCurvature %f
    inData: (a float)
            Data weight
            flag: --inData %f
    inFLAIR: (an existing file name)
            FLAIR Image
            flag: --inFLAIR %s
    inMP2RAGE: (an existing file name)
            MP2RAGE T1 Map Image
            flag: --inMP2RAGE %s
    inMP2RAGE2: (an existing file name)
            MP2RAGE T1-weighted Image
            flag: --inMP2RAGE2 %s
    inMPRAGE: (an existing file name)
            MPRAGE T1-weighted Image
            flag: --inMPRAGE %s
    inMax: (an integer)
            Max iterations
            flag: --inMax %d
    inMin: (a float)
            Min change
            flag: --inMin %f
    inOutput: ('segmentation' or 'memberships')
            Output images
            flag: --inOutput %s
    inPV: (an existing file name)
            PV / Dura Image
            flag: --inPV %s
    inPosterior: (a float)
            Posterior scale (mm)
            flag: --inPosterior %f
    inSteps: (an integer)
            Steps
            flag: --inSteps %d
    inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
             or 'wco' or 'no')
            Topology
            flag: --inTopology %s
    null: (a string)
            Execution Time
            flag: --null %s
    outLevelset: (a boolean or a file name)
            Levelset Boundary Image
            flag: --outLevelset %s
    outPosterior2: (a boolean or a file name)
            Posterior Maximum Memberships (4D)
            flag: --outPosterior2 %s
    outPosterior3: (a boolean or a file name)
            Posterior Maximum Labels (4D)
            flag: --outPosterior3 %s
    outSegmented: (a boolean or a file name)
            Segmented Brain Image
            flag: --outSegmented %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outLevelset: (an existing file name)
            Levelset Boundary Image
    outPosterior2: (an existing file name)
            Posterior Maximum Memberships (4D)
    outPosterior3: (an existing file name)
            Posterior Maximum Labels (4D)
    outSegmented: (an existing file name)
            Segmented Brain Image

## JistBrainMp2rageDuraEstimation

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.brain.JistBrainMp2rageDuraEstimation **

title: MP2RAGE Dura Estimation

category: Developer Tools

description: Filters a MP2RAGE brain image to obtain a probability map of dura matter.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inDistance: (a float)
            Distance to background (mm)
            flag: --inDistance %f
    inSecond: (an existing file name)
            Second inversion (Inv2) Image
            flag: --inSecond %s
    inSkull: (an existing file name)
            Skull Stripping Mask
            flag: --inSkull %s
    inoutput: ('dura_region' or 'boundary' or 'dura_prior' or 'bg_prior'
             or 'intens_prior')
            Outputs an estimate of the dura / CSF boundary or an estimate of the
            entire dura region.
            flag: --inoutput %s
    null: (a string)
            Execution Time
            flag: --null %s
    outDura: (a boolean or a file name)
            Dura Image
            flag: --outDura %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outDura: (an existing file name)
            Dura Image

## JistBrainMp2rageSkullStripping

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.brain.JistBrainMp2rageSkullStripping **

title: MP2RAGE Skull Stripping

category: Developer Tools

description: Estimate a brain mask for a MP2RAGE dataset. At least a T1-weighted or a T1 map image is required.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inFilter: (an existing file name)
            Filter Image (opt)
            flag: --inFilter %s
    inSecond: (an existing file name)
            Second inversion (Inv2) Image
            flag: --inSecond %s
    inSkip: ('true' or 'false')
            Skip zero values
            flag: --inSkip %s
    inT1: (an existing file name)
            T1 Map (T1_Images) Image (opt)
            flag: --inT1 %s
    inT1weighted: (an existing file name)
            T1-weighted (UNI) Image (opt)
            flag: --inT1weighted %s
    null: (a string)
            Execution Time
            flag: --null %s
    outBrain: (a boolean or a file name)
            Brain Mask Image
            flag: --outBrain %s
    outMasked: (a boolean or a file name)
            Masked T1 Map Image
            flag: --outMasked %s
    outMasked2: (a boolean or a file name)
            Masked T1-weighted Image
            flag: --outMasked2 %s
    outMasked3: (a boolean or a file name)
            Masked Filter Image
            flag: --outMasked3 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outBrain: (an existing file name)
            Brain Mask Image
    outMasked: (an existing file name)
            Masked T1 Map Image
    outMasked2: (an existing file name)
            Masked T1-weighted Image
    outMasked3: (an existing file name)
            Masked Filter Image

## JistBrainPartialVolumeFilter

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.brain.JistBrainPartialVolumeFilter **

title: Partial Volume Filter

category: Developer Tools

description: Filters an image for regions of partial voluming assuming a ridge-like model of intensity.

version: 2.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inInput: (an existing file name)
            Input Image
            flag: --inInput %s
    inPV: ('bright' or 'dark' or 'both')
            Outputs the raw intensity values or a probability score for the
            partial volume regions.
            flag: --inPV %s
    inoutput: ('probability' or 'intensity')
            output
            flag: --inoutput %s
    null: (a string)
            Execution Time
            flag: --null %s
    outPartial: (a boolean or a file name)
            Partial Volume Image
            flag: --outPartial %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outPartial: (an existing file name)
            Partial Volume Image

## JistCortexSurfaceMeshInflation

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.cortex.JistCortexSurfaceMeshInflation **

title: Surface Mesh Inflation

category: Developer Tools

description: Inflates a cortical surface mesh. D. Tosun, M. E. Rettmann, X. Han, X. Tao, C. Xu, S. M. Resnick, D. Pham, and J. L. Prince, Cortical Surface Segmentation and Mapping, NeuroImage, vol. 23, pp. S108–S118, 2004.

version: 3.0.RC

contributor: Duygu Tosun

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inLevelset: (an existing file name)
            Levelset Image
            flag: --inLevelset %s
    inLorentzian: ('true' or 'false')
            Lorentzian Norm
            flag: --inLorentzian %s
    inMax: (an integer)
            Max Iterations
            flag: --inMax %d
    inMean: (a float)
            Mean Curvature Threshold
            flag: --inMean %f
    inSOR: (a float)
            SOR Parameter
            flag: --inSOR %f
    inStep: (an integer)
            Step Size
            flag: --inStep %d
    inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
             or 'wco' or 'no')
            Topology
            flag: --inTopology %s
    null: (a string)
            Execution Time
            flag: --null %s
    outInflated: (a boolean or a file name)
            Inflated Surface
            flag: --outInflated %s
    outOriginal: (a boolean or a file name)
            Original Surface
            flag: --outOriginal %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outInflated: (an existing file name)
            Inflated Surface
    outOriginal: (an existing file name)
            Original Surface

## JistIntensityMp2rageMasking

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.intensity.JistIntensityMp2rageMasking **

title: MP2RAGE Background Masking

category: Developer Tools

description: Estimate a background signal mask for a MP2RAGE dataset.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inBackground: ('exponential' or 'half-normal')
            Model distribution for background noise (default is half-normal,
            exponential is more stringent).
            flag: --inBackground %s
    inMasking: ('binary' or 'proba')
            Whether to use a binary threshold or a weighted average based on the
            probability.
            flag: --inMasking %s
    inQuantitative: (an existing file name)
            Quantitative T1 Map (T1_Images) Image
            flag: --inQuantitative %s
    inSecond: (an existing file name)
            Second inversion (Inv2) Image
            flag: --inSecond %s
    inSkip: ('true' or 'false')
            Skip zero values
            flag: --inSkip %s
    inT1weighted: (an existing file name)
            T1-weighted (UNI) Image
            flag: --inT1weighted %s
    null: (a string)
            Execution Time
            flag: --null %s
    outMasked: (a boolean or a file name)
            Masked T1 Map Image
            flag: --outMasked %s
    outMasked2: (a boolean or a file name)
            Masked Iso Image
            flag: --outMasked2 %s
    outSignal: (a boolean or a file name)
            Signal Proba Image
            flag: --outSignal %s
    outSignal2: (a boolean or a file name)
            Signal Mask Image
            flag: --outSignal2 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outMasked: (an existing file name)
            Masked T1 Map Image
    outMasked2: (an existing file name)
            Masked Iso Image
    outSignal: (an existing file name)
            Signal Proba Image
    outSignal2: (an existing file name)
            Signal Mask Image

## JistLaminarProfileCalculator

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.laminar.JistLaminarProfileCalculator **

title: Profile Calculator

category: Developer Tools

description: Compute various moments for intensities mapped along a cortical profile.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inIntensity: (an existing file name)
            Intensity Profile Image
            flag: --inIntensity %s
    inMask: (an existing file name)
            Mask Image (opt, 3D or 4D)
            flag: --inMask %s
    incomputed: ('mean' or 'stdev' or 'skewness' or 'kurtosis')
            computed statistic
            flag: --incomputed %s
    null: (a string)
            Execution Time
            flag: --null %s
    outResult: (a boolean or a file name)
            Result
            flag: --outResult %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outResult: (an existing file name)
            Result

## JistLaminarProfileGeometry

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.laminar.JistLaminarProfileGeometry **

title: Profile Geometry

category: Developer Tools

description: Compute various geometric quantities for a cortical layers.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inProfile: (an existing file name)
            Profile Surface Image
            flag: --inProfile %s
    incomputed: ('thickness' or 'curvedness' or 'shape_index' or
             'mean_curvature' or 'gauss_curvature' or 'profile_length' or
             'profile_curvature' or 'profile_torsion')
            computed measure
            flag: --incomputed %s
    inoutside: (a float)
            outside extension (mm)
            flag: --inoutside %f
    inregularization: ('none' or 'Gaussian')
            regularization
            flag: --inregularization %s
    insmoothing: (a float)
            smoothing parameter
            flag: --insmoothing %f
    null: (a string)
            Execution Time
            flag: --null %s
    outResult: (a boolean or a file name)
            Result
            flag: --outResult %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outResult: (an existing file name)
            Result

## JistLaminarProfileSampling

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.laminar.JistLaminarProfileSampling **

title: Profile Sampling

category: Developer Tools

description: Sample some intensity image along a cortical profile across layer surfaces.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inCortex: (an existing file name)
            Cortex Mask (opt)
            flag: --inCortex %s
    inIntensity: (an existing file name)
            Intensity Image
            flag: --inIntensity %s
    inProfile: (an existing file name)
            Profile Surface Image
            flag: --inProfile %s
    null: (a string)
            Execution Time
            flag: --null %s
    outProfile2: (a boolean or a file name)
            Profile 4D Mask
            flag: --outProfile2 %s
    outProfilemapped: (a boolean or a file name)
            Profile-mapped Intensity Image
            flag: --outProfilemapped %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outProfile2: (an existing file name)
            Profile 4D Mask
    outProfilemapped: (an existing file name)
            Profile-mapped Intensity Image

## JistLaminarROIAveraging

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.laminar.JistLaminarROIAveraging **

title: Profile ROI Averaging

category: Developer Tools

description: Compute an average profile over a given ROI.

version: 3.0.RC

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inIntensity: (an existing file name)
            Intensity Profile Image
            flag: --inIntensity %s
    inMask: (an existing file name)
            Mask Image (opt, 3D or 4D)
            flag: --inMask %s
    inROI: (an existing file name)
            ROI Mask
            flag: --inROI %s
    inROI2: (a string)
            ROI Name
            flag: --inROI2 %s
    null: (a string)
            Execution Time
            flag: --null %s
    outROI3: (a boolean or a file name)
            ROI Average
            flag: --outROI3 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outROI3: (an existing file name)
            ROI Average

## JistLaminarVolumetricLayering

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run de.mpg.cbs.jist.laminar.JistLaminarVolumetricLayering **

title: Volumetric Layering

category: Developer Tools

description: Builds a continuous layering of the cortex following distance-preserving or volume-preserving models of cortical folding. Waehnert MD, Dinse J, Weiss M, Streicher MN, Waehnert P, Geyer S, Turner R, Bazin PL, Anatomically motivated modeling of cortical laminae, Neuroimage, 2013.

version: 3.0.RC

contributor: Miriam Waehnert (waehnert@cbs.mpg.de) http://www.cbs.mpg.de/

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inInner: (an existing file name)
            Inner Distance Image (GM/WM boundary)
            flag: --inInner %s
    inLayering: ('distance-preserving' or 'volume-preserving')
            Layering method
            flag: --inLayering %s
    inLayering2: ('outward' or 'inward')
            Layering direction
            flag: --inLayering2 %s
    inMax: (an integer)
            Max iterations for narrow band evolution
            flag: --inMax %d
    inMin: (a float)
            Min change ratio for narrow band evolution
            flag: --inMin %f
    inNumber: (an integer)
            Number of layers
            flag: --inNumber %d
    inOuter: (an existing file name)
            Outer Distance Image (CSF/GM boundary)
            flag: --inOuter %s
    inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
             or 'wco' or 'no')
            Topology
            flag: --inTopology %s
    incurvature: (an integer)
            curvature approximation scale (voxels)
            flag: --incurvature %d
    inpresmooth: ('true' or 'false')
            pre-smooth cortical surfaces
            flag: --inpresmooth %s
    inratio: (a float)
            ratio smoothing kernel size (voxels)
            flag: --inratio %f
    null: (a string)
            Execution Time
            flag: --null %s
    outContinuous: (a boolean or a file name)
            Continuous depth measurement
            flag: --outContinuous %s
    outDiscrete: (a boolean or a file name)
            Discrete sampled layers
            flag: --outDiscrete %s
    outLayer: (a boolean or a file name)
            Layer boundary surfaces
            flag: --outLayer %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outContinuous: (an existing file name)
            Continuous depth measurement
    outDiscrete: (an existing file name)
            Discrete sampled layers
    outLayer: (an existing file name)
            Layer boundary surfaces

## MedicAlgorithmImageCalculator

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.utilities.math.MedicAlgorithmImageCalculator **

title: Image Calculator

category: Developer Tools

description: Perform simple image calculator operations on two images. The operations include ‘Add’, ‘Subtract’, ‘Multiply’, and ‘Divide’

version: 1.10.RC

documentation-url: http://www.iacl.ece.jhu.edu/

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inOperation: ('Add' or 'Subtract' or 'Multiply' or 'Divide' or 'Min'
             or 'Max')
            Operation
            flag: --inOperation %s
    inVolume: (an existing file name)
            Volume 1
            flag: --inVolume %s
    inVolume2: (an existing file name)
            Volume 2
            flag: --inVolume2 %s
    null: (a string)
            Execution Time
            flag: --null %s
    outResult: (a boolean or a file name)
            Result Volume
            flag: --outResult %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outResult: (an existing file name)
            Result Volume

## MedicAlgorithmLesionToads

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.classification.MedicAlgorithmLesionToads **

title: Lesion TOADS

category: Developer Tools

description: Algorithm for simulataneous brain structures and MS lesion segmentation of MS Brains. The brain segmentation is topologically consistent and the algorithm can use multiple MR sequences as input data. N. Shiee, P.-L. Bazin, A.Z. Ozturk, P.A. Calabresi, D.S. Reich, D.L. Pham, “A Topology-Preserving Approach to the Segmentation of Brain Images with Multiple Sclerosis”, NeuroImage, vol. 49, no. 2, pp. 1524-1535, 2010.

version: 1.9.R

contributor: Navid Shiee (navid.shiee@nih.gov) http://iacl.ece.jhu.edu/~nshiee/

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inAtlas: ('With Lesion' or 'No Lesion')
            Atlas to Use
            flag: --inAtlas %s
    inAtlas2: (an existing file name)
            Atlas File - With Lesions
            flag: --inAtlas2 %s
    inAtlas3: (an existing file name)
            Atlas File - No Lesion - T1 and FLAIR
            flag: --inAtlas3 %s
    inAtlas4: (an existing file name)
            Atlas File - No Lesion - T1 Only
            flag: --inAtlas4 %s
    inAtlas5: (a float)
            Controls the effect of the statistical atlas on the segmentation
            flag: --inAtlas5 %f
    inAtlas6: ('rigid' or 'multi_fully_affine')
            Atlas alignment
            flag: --inAtlas6 %s
    inConnectivity: ('(26,6)' or '(6,26)' or '(6,18)' or '(18,6)')
            Connectivity (foreground,background)
            flag: --inConnectivity %s
    inCorrect: ('true' or 'false')
            Correct MR field inhomogeneity.
            flag: --inCorrect %s
    inFLAIR: (an existing file name)
            FLAIR Image
            flag: --inFLAIR %s
    inInclude: ('true' or 'false')
            Include lesion in WM class in hard classification
            flag: --inInclude %s
    inMaximum: (an integer)
            Maximum distance from the interventricular WM boundary to downweight
            the lesion membership to avoid false postives
            flag: --inMaximum %d
    inMaximum2: (an integer)
            Maximum Ventircle Distance
            flag: --inMaximum2 %d
    inMaximum3: (an integer)
            Maximum InterVentricular Distance
            flag: --inMaximum3 %d
    inMaximum4: (a float)
            Maximum amount of relative change in the energy function considered
            as the convergence criteria
            flag: --inMaximum4 %f
    inMaximum5: (an integer)
            Maximum iterations
            flag: --inMaximum5 %d
    inOutput: ('hard segmentation' or 'hard segmentation+memberships' or
             'cruise inputs' or 'dura removal inputs')
            Output images
            flag: --inOutput %s
    inOutput2: ('true' or 'false')
            Output the hard classification using maximum membership (not
            neceesarily topologically correct)
            flag: --inOutput2 %s
    inOutput3: ('true' or 'false')
            Output the estimated inhomogeneity field
            flag: --inOutput3 %s
    inSmooting: (a float)
            Controls the effect of neighberhood voxels on the membership
            flag: --inSmooting %f
    inT1_MPRAGE: (an existing file name)
            T1_MPRAGE Image
            flag: --inT1_MPRAGE %s
    inT1_SPGR: (an existing file name)
            T1_SPGR Image
            flag: --inT1_SPGR %s
    null: (a string)
            Execution Time
            flag: --null %s
    outCortical: (a boolean or a file name)
            Cortical GM Membership
            flag: --outCortical %s
    outFilled: (a boolean or a file name)
            Filled WM Membership
            flag: --outFilled %s
    outHard: (a boolean or a file name)
            Hard segmentation
            flag: --outHard %s
    outHard2: (a boolean or a file name)
            Hard segmentationfrom memberships
            flag: --outHard2 %s
    outInhomogeneity: (a boolean or a file name)
            Inhomogeneity Field
            flag: --outInhomogeneity %s
    outLesion: (a boolean or a file name)
            Lesion Segmentation
            flag: --outLesion %s
    outMembership: (a boolean or a file name)
            Membership Functions
            flag: --outMembership %s
    outSulcal: (a boolean or a file name)
            Sulcal CSF Membership
            flag: --outSulcal %s
    outWM: (a boolean or a file name)
            WM Mask
            flag: --outWM %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outCortical: (an existing file name)
            Cortical GM Membership
    outFilled: (an existing file name)
            Filled WM Membership
    outHard: (an existing file name)
            Hard segmentation
    outHard2: (an existing file name)
            Hard segmentationfrom memberships
    outInhomogeneity: (an existing file name)
            Inhomogeneity Field
    outLesion: (an existing file name)
            Lesion Segmentation
    outMembership: (an existing file name)
            Membership Functions
    outSulcal: (an existing file name)
            Sulcal CSF Membership
    outWM: (an existing file name)
            WM Mask

## MedicAlgorithmMipavReorient

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.utilities.volume.MedicAlgorithmMipavReorient **

title: Reorient Volume

category: Developer Tools

description: Reorient a volume to a particular anatomical orientation.

version: .alpha

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inInterpolation: ('Nearest Neighbor' or 'Trilinear' or 'Bspline 3rd
             order' or 'Bspline 4th order' or 'Cubic Lagrangian' or 'Quintic
             Lagrangian' or 'Heptic Lagrangian' or 'Windowed Sinc')
            Interpolation
            flag: --inInterpolation %s
    inNew: ('Dicom axial' or 'Dicom coronal' or 'Dicom sagittal' or 'User
             defined')
            New image orientation
            flag: --inNew %s
    inResolution: ('Unchanged' or 'Finest cubic' or 'Coarsest cubic' or
             'Same as template')
            Resolution
            flag: --inResolution %s
    inSource: (a list of items which are a file name)
            Source
            flag: --inSource %s
    inTemplate: (an existing file name)
            Template
            flag: --inTemplate %s
    inUser: ('Unknown' or 'Patient Right to Left' or 'Patient Left to
             Right' or 'Patient Posterior to Anterior' or 'Patient Anterior to
             Posterior' or 'Patient Inferior to Superior' or 'Patient Superior
             to Inferior')
            User defined X-axis orientation (image left to right)
            flag: --inUser %s
    inUser2: ('Unknown' or 'Patient Right to Left' or 'Patient Left to
             Right' or 'Patient Posterior to Anterior' or 'Patient Anterior to
             Posterior' or 'Patient Inferior to Superior' or 'Patient Superior
             to Inferior')
            User defined Y-axis orientation (image top to bottom)
            flag: --inUser2 %s
    inUser3: ('Unknown' or 'Patient Right to Left' or 'Patient Left to
             Right' or 'Patient Posterior to Anterior' or 'Patient Anterior to
             Posterior' or 'Patient Inferior to Superior' or 'Patient Superior
             to Inferior')
            User defined Z-axis orientation (into the screen)
            flag: --inUser3 %s
    inUser4: ('Axial' or 'Coronal' or 'Sagittal' or 'Unknown')
            User defined Image Orientation
            flag: --inUser4 %s
    null: (a string)
            Execution Time
            flag: --null %s
    outReoriented: (a list of items which are a file name)
            Reoriented Volume
            flag: --outReoriented %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    None

## MedicAlgorithmN3

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.classification.MedicAlgorithmN3 **

title: N3 Correction

category: Developer Tools

description: Non-parametric Intensity Non-uniformity Correction, N3, originally by J.G. Sled.

version: 1.8.R

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inAutomatic: ('true' or 'false')
            If true determines the threshold by histogram analysis. If true a
            VOI cannot be used and the input threshold is ignored.
            flag: --inAutomatic %s
    inEnd: (a float)
            Usually 0.01-0.00001, The measure used to terminate the iterations
            is the coefficient of variation of change in field estimates between
            successive iterations.
            flag: --inEnd %f
    inField: (a float)
            Characteristic distance over which the field varies. The distance
            between adjacent knots in bspline fitting with at least 4 knots
            going in every dimension. The default in the dialog is one third the
            distance (resolution * extents) of the smallest dimension.
            flag: --inField %f
    inInput: (an existing file name)
            Input Volume
            flag: --inInput %s
    inKernel: (a float)
            Usually between 0.05-0.50, Width of deconvolution kernel used to
            sharpen the histogram. Larger values give faster convergence while
            smaller values give greater accuracy.
            flag: --inKernel %f
    inMaximum: (an integer)
            Maximum number of Iterations
            flag: --inMaximum %d
    inSignal: (a float)
            Default = min + 1, Values at less than threshold are treated as part
            of the background
            flag: --inSignal %f
    inSubsample: (a float)
            Usually between 1-32, The factor by which the data is subsampled to
            a lower resolution in estimating the slowly varying non-uniformity
            field. Reduce sampling in the finest sampling direction by the
            shrink factor.
            flag: --inSubsample %f
    inWeiner: (a float)
            Usually between 0.0-1.0
            flag: --inWeiner %f
    null: (a string)
            Execution Time
            flag: --null %s
    outInhomogeneity: (a boolean or a file name)
            Inhomogeneity Corrected Volume
            flag: --outInhomogeneity %s
    outInhomogeneity2: (a boolean or a file name)
            Inhomogeneity Field
            flag: --outInhomogeneity2 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outInhomogeneity: (an existing file name)
            Inhomogeneity Corrected Volume
    outInhomogeneity2: (an existing file name)
            Inhomogeneity Field

## MedicAlgorithmSPECTRE2010

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.segmentation.skull_strip.MedicAlgorithmSPECTRE2010 **

title: SPECTRE 2010

category: Developer Tools

### description: Simple Paradigm for Extra-Cranial Tissue REmoval

Algorithm Version: 1.6 GUI Version: 1.10

A. Carass, M.B. Wheeler, J. Cuzzocreo, P.-L. Bazin, S.S. Bassett, and J.L. Prince, ‘A Joint Registration and Segmentation Approach to Skull Stripping’, Fourth IEEE International Symposium on Biomedical Imaging (ISBI 2007), Arlington, VA, April 12-15, 2007. A. Carass, J. Cuzzocreo, M.B. Wheeler, P.-L. Bazin, S.M. Resnick, and J.L. Prince, ‘Simple paradigm for extra-cerebral tissue removal: Algorithm and analysis’, NeuroImage 56(4):1982-1992, 2011.

version: 1.6.R

documentation-url: http://www.iacl.ece.jhu.edu/

contributor: Aaron Carass (aaron_carass@jhu.edu) http://www.iacl.ece.jhu.edu/ Hanlin Wan (hanlinwan@gmail.com)

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inApply: ('All' or 'X' or 'Y' or 'Z')
            Apply rotation
            flag: --inApply %s
    inAtlas: (an existing file name)
            SPECTRE atlas description file. A text file enumerating atlas files
            and landmarks.
            flag: --inAtlas %s
    inBackground: (a float)
            flag: --inBackground %f
    inCoarse: (a float)
            Coarse angle increment
            flag: --inCoarse %f
    inCost: ('Correlation ratio' or 'Least squares' or 'Normalized cross
             correlation' or 'Normalized mutual information')
            Cost function
            flag: --inCost %s
    inDegrees: ('Rigid - 6' or 'Global rescale - 7' or 'Specific rescale
             - 9' or 'Affine - 12')
            Degrees of freedom
            flag: --inDegrees %s
    inFind: ('true' or 'false')
            Find Midsaggital Plane
            flag: --inFind %s
    inFine: (a float)
            Fine angle increment
            flag: --inFine %f
    inImage: ('T1_SPGR' or 'T1_ALT' or 'T1_MPRAGE' or 'T2' or 'FLAIR')
            Set the image modality. MP-RAGE is recommended for most T1 sequence
            images.
            flag: --inImage %s
    inInhomogeneity: ('true' or 'false')
            Set to false by default, this parameter will make FANTASM try to do
            inhomogeneity correction during it's iterative cycle.
            flag: --inInhomogeneity %s
    inInitial: (an integer)
            Erosion of the inital mask, which is based on the probability mask
            and the classification., The initial mask is ouput as the d0 volume
            at the conclusion of SPECTRE.
            flag: --inInitial %d
    inInitial2: (a float)
            Initial probability threshold
            flag: --inInitial2 %f
    inInput: (an existing file name)
            Input volume to be skullstripped.
            flag: --inInput %s
    inMMC: (an integer)
            The size of the dilation step within the Modified Morphological
            Closing.
            flag: --inMMC %d
    inMMC2: (an integer)
            The size of the erosion step within the Modified Morphological
            Closing.
            flag: --inMMC2 %d
    inMaximum: (a float)
            Maximum angle
            flag: --inMaximum %f
    inMinimum: (a float)
            Minimum probability threshold
            flag: --inMinimum %f
    inMinimum2: (a float)
            Minimum angle
            flag: --inMinimum2 %f
    inMultiple: (an integer)
            Multiple of tolerance to bracket the minimum
            flag: --inMultiple %d
    inMultithreading: ('true' or 'false')
            Set to false by default, this parameter controls the multithreaded
            behavior of the linear registration.
            flag: --inMultithreading %s
    inNumber: (an integer)
            Number of iterations
            flag: --inNumber %d
    inNumber2: (an integer)
            Number of minima from Level 8 to test at Level 4
            flag: --inNumber2 %d
    inOutput: ('true' or 'false')
            Determines if the output results are transformed back into the space
            of the original input image.
            flag: --inOutput %s
    inOutput2: ('true' or 'false')
            Output Plane?
            flag: --inOutput2 %s
    inOutput3: ('true' or 'false')
            Output Split-Halves?
            flag: --inOutput3 %s
    inOutput4: ('true' or 'false')
            Output Segmentation on Plane?
            flag: --inOutput4 %s
    inOutput5: ('Trilinear' or 'Bspline 3rd order' or 'Bspline 4th order'
             or 'Cubic Lagrangian' or 'Quintic Lagrangian' or 'Heptic
             Lagrangian' or 'Windowed sinc' or 'Nearest Neighbor')
            Output interpolation
            flag: --inOutput5 %s
    inRegistration: ('Trilinear' or 'Bspline 3rd order' or 'Bspline 4th
             order' or 'Cubic Lagrangian' or 'Quintic Lagrangian' or 'Heptic
             Lagrangian' or 'Windowed sinc')
            Registration interpolation
            flag: --inRegistration %s
    inResample: ('true' or 'false')
            Determines if the data is resampled to be isotropic during the
            processing.
            flag: --inResample %s
    inRun: ('true' or 'false')
            Run Smooth Brain Mask
            flag: --inRun %s
    inSkip: ('true' or 'false')
            Skip multilevel search (Assume images are close to alignment)
            flag: --inSkip %s
    inSmoothing: (a float)
            flag: --inSmoothing %f
    inSubsample: ('true' or 'false')
            Subsample image for speed
            flag: --inSubsample %s
    inUse: ('true' or 'false')
            Use the max of the min resolutions of the two datasets when
            resampling
            flag: --inUse %s
    null: (a string)
            Execution Time
            flag: --null %s
    outFANTASM: (a boolean or a file name)
            Tissue classification of of the whole input volume.
            flag: --outFANTASM %s
    outMask: (a boolean or a file name)
            Binary Mask of the skullstripped result with just the brain
            flag: --outMask %s
    outMidsagittal: (a boolean or a file name)
            Plane dividing the brain hemispheres
            flag: --outMidsagittal %s
    outOriginal: (a boolean or a file name)
            If Output in Original Space Flag is true then outputs the original
            input volume. Otherwise outputs the axialy reoriented input volume.
            flag: --outOriginal %s
    outPrior: (a boolean or a file name)
            Probability prior from the atlas registrations
            flag: --outPrior %s
    outSegmentation: (a boolean or a file name)
            2D image showing the tissue classification on the midsagittal plane
            flag: --outSegmentation %s
    outSplitHalves: (a boolean or a file name)
            Skullstripped mask of the brain with the hemispheres divided.
            flag: --outSplitHalves %s
    outStripped: (a boolean or a file name)
            Skullstripped result of the input volume with just the brain.
            flag: --outStripped %s
    outd0: (a boolean or a file name)
            Initial Brainmask
            flag: --outd0 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outFANTASM: (an existing file name)
            Tissue classification of of the whole input volume.
    outMask: (an existing file name)
            Binary Mask of the skullstripped result with just the brain
    outMidsagittal: (an existing file name)
            Plane dividing the brain hemispheres
    outOriginal: (an existing file name)
            If Output in Original Space Flag is true then outputs the original
            input volume. Otherwise outputs the axialy reoriented input volume.
    outPrior: (an existing file name)
            Probability prior from the atlas registrations
    outSegmentation: (an existing file name)
            2D image showing the tissue classification on the midsagittal plane
    outSplitHalves: (an existing file name)
            Skullstripped mask of the brain with the hemispheres divided.
    outStripped: (an existing file name)
            Skullstripped result of the input volume with just the brain.
    outd0: (an existing file name)
            Initial Brainmask

## MedicAlgorithmThresholdToBinaryMask

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.ece.iacl.plugins.utilities.volume.MedicAlgorithmThresholdToBinaryMask **

title: Threshold to Binary Mask

category: Developer Tools

description: Given a volume and an intensity range create a binary mask for values within that range.

version: 1.2.RC

documentation-url: http://www.iacl.ece.jhu.edu/

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inLabel: (a list of items which are a file name)
            Input volumes
            flag: --inLabel %s
    inMaximum: (a float)
            Maximum threshold value.
            flag: --inMaximum %f
    inMinimum: (a float)
            Minimum threshold value.
            flag: --inMinimum %f
    inUse: ('true' or 'false')
            Use the images max intensity as the max value of the range.
            flag: --inUse %s
    null: (a string)
            Execution Time
            flag: --null %s
    outBinary: (a list of items which are a file name)
            Binary Mask
            flag: --outBinary %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    None

## RandomVol

Link to code

Wraps command **java edu.jhu.ece.iacl.jist.cli.run edu.jhu.bme.smile.demo.RandomVol **

title: Random Volume Generator

category: Developer Tools

description: Generate a random scalar volume.

version: 1.12.RC

documentation-url: http://www.nitrc.org/projects/jist/

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    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
    inField: ('Uniform' or 'Normal' or 'Exponential')
            Field
            flag: --inField %s
    inLambda: (a float)
            Lambda Value for Exponential Distribution
            flag: --inLambda %f
    inMaximum: (an integer)
            Maximum Value
            flag: --inMaximum %d
    inMinimum: (an integer)
            Minimum Value
            flag: --inMinimum %d
    inSize: (an integer)
            Size of Volume in X direction
            flag: --inSize %d
    inSize2: (an integer)
            Size of Volume in Y direction
            flag: --inSize2 %d
    inSize3: (an integer)
            Size of Volume in Z direction
            flag: --inSize3 %d
    inSize4: (an integer)
            Size of Volume in t direction
            flag: --inSize4 %d
    inStandard: (an integer)
            Standard Deviation for Normal Distribution
            flag: --inStandard %d
    null: (a string)
            Execution Time
            flag: --null %s
    outRand1: (a boolean or a file name)
            Rand1
            flag: --outRand1 %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal immediately
            (default), `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    xDefaultMem: (an integer)
            Set default maximum heap size
            flag: -xDefaultMem %d
    xMaxProcess: (an integer, nipype default value: 1)
            Set default maximum number of processes.
            flag: -xMaxProcess %d
    xPrefExt: ('nrrd')
            Output File Type
            flag: --xPrefExt %s

Outputs:

    outRand1: (an existing file name)
            Rand1