interfaces.mipav.developer

JistBrainMgdmSegmentation

Link to code

Wraps the executable 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:

[Optional]
inMP2RAGE: (an existing file name)
        MP2RAGE T1 Map Image
        argument: ``--inMP2RAGE %s``
inMP2RAGE2: (an existing file name)
        MP2RAGE T1-weighted Image
        argument: ``--inMP2RAGE2 %s``
inPV: (an existing file name)
        PV / Dura Image
        argument: ``--inPV %s``
inMPRAGE: (an existing file name)
        MPRAGE T1-weighted Image
        argument: ``--inMPRAGE %s``
inFLAIR: (an existing file name)
        FLAIR Image
        argument: ``--inFLAIR %s``
inAtlas: (an existing file name)
        Atlas file
        argument: ``--inAtlas %s``
inData: (a float)
        Data weight
        argument: ``--inData %f``
inCurvature: (a float)
        Curvature weight
        argument: ``--inCurvature %f``
inPosterior: (a float)
        Posterior scale (mm)
        argument: ``--inPosterior %f``
inMax: (an integer (int or long))
        Max iterations
        argument: ``--inMax %d``
inMin: (a float)
        Min change
        argument: ``--inMin %f``
inSteps: (an integer (int or long))
        Steps
        argument: ``--inSteps %d``
inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
          or 'wco' or 'no')
        Topology
        argument: ``--inTopology %s``
inCompute: ('true' or 'false')
        Compute posteriors
        argument: ``--inCompute %s``
inAdjust: ('true' or 'false')
        Adjust intensity priors
        argument: ``--inAdjust %s``
inOutput: ('segmentation' or 'memberships')
        Output images
        argument: ``--inOutput %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outSegmented: (a boolean or a file name)
        Segmented Brain Image
        argument: ``--outSegmented %s``
outLevelset: (a boolean or a file name)
        Levelset Boundary Image
        argument: ``--outLevelset %s``
outPosterior2: (a boolean or a file name)
        Posterior Maximum Memberships (4D)
        argument: ``--outPosterior2 %s``
outPosterior3: (a boolean or a file name)
        Posterior Maximum Labels (4D)
        argument: ``--outPosterior3 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outSegmented: (an existing file name)
        Segmented Brain Image
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)

JistBrainMp2rageDuraEstimation

Link to code

Wraps the executable 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:

[Optional]
inSecond: (an existing file name)
        Second inversion (Inv2) Image
        argument: ``--inSecond %s``
inSkull: (an existing file name)
        Skull Stripping Mask
        argument: ``--inSkull %s``
inDistance: (a float)
        Distance to background (mm)
        argument: ``--inDistance %f``
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.
        argument: ``--inoutput %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outDura: (a boolean or a file name)
        Dura Image
        argument: ``--outDura %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outDura: (an existing file name)
        Dura Image

JistBrainMp2rageSkullStripping

Link to code

Wraps the executable 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:

[Optional]
inSecond: (an existing file name)
        Second inversion (Inv2) Image
        argument: ``--inSecond %s``
inT1: (an existing file name)
        T1 Map (T1_Images) Image (opt)
        argument: ``--inT1 %s``
inT1weighted: (an existing file name)
        T1-weighted (UNI) Image (opt)
        argument: ``--inT1weighted %s``
inFilter: (an existing file name)
        Filter Image (opt)
        argument: ``--inFilter %s``
inSkip: ('true' or 'false')
        Skip zero values
        argument: ``--inSkip %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outBrain: (a boolean or a file name)
        Brain Mask Image
        argument: ``--outBrain %s``
outMasked: (a boolean or a file name)
        Masked T1 Map Image
        argument: ``--outMasked %s``
outMasked2: (a boolean or a file name)
        Masked T1-weighted Image
        argument: ``--outMasked2 %s``
outMasked3: (a boolean or a file name)
        Masked Filter Image
        argument: ``--outMasked3 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

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 the executable 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:

[Optional]
inInput: (an existing file name)
        Input Image
        argument: ``--inInput %s``
inPV: ('bright' or 'dark' or 'both')
        Outputs the raw intensity values or a probability score for the
        partial volume regions.
        argument: ``--inPV %s``
inoutput: ('probability' or 'intensity')
        output
        argument: ``--inoutput %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outPartial: (a boolean or a file name)
        Partial Volume Image
        argument: ``--outPartial %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outPartial: (an existing file name)
        Partial Volume Image

JistCortexSurfaceMeshInflation

Link to code

Wraps the executable 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:

[Optional]
inLevelset: (an existing file name)
        Levelset Image
        argument: ``--inLevelset %s``
inSOR: (a float)
        SOR Parameter
        argument: ``--inSOR %f``
inMean: (a float)
        Mean Curvature Threshold
        argument: ``--inMean %f``
inStep: (an integer (int or long))
        Step Size
        argument: ``--inStep %d``
inMax: (an integer (int or long))
        Max Iterations
        argument: ``--inMax %d``
inLorentzian: ('true' or 'false')
        Lorentzian Norm
        argument: ``--inLorentzian %s``
inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
          or 'wco' or 'no')
        Topology
        argument: ``--inTopology %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outOriginal: (a boolean or a file name)
        Original Surface
        argument: ``--outOriginal %s``
outInflated: (a boolean or a file name)
        Inflated Surface
        argument: ``--outInflated %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

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

JistIntensityMp2rageMasking

Link to code

Wraps the executable 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:

[Optional]
inSecond: (an existing file name)
        Second inversion (Inv2) Image
        argument: ``--inSecond %s``
inQuantitative: (an existing file name)
        Quantitative T1 Map (T1_Images) Image
        argument: ``--inQuantitative %s``
inT1weighted: (an existing file name)
        T1-weighted (UNI) Image
        argument: ``--inT1weighted %s``
inBackground: ('exponential' or 'half-normal')
        Model distribution for background noise (default is half-normal,
        exponential is more stringent).
        argument: ``--inBackground %s``
inSkip: ('true' or 'false')
        Skip zero values
        argument: ``--inSkip %s``
inMasking: ('binary' or 'proba')
        Whether to use a binary threshold or a weighted average based on the
        probability.
        argument: ``--inMasking %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outSignal: (a boolean or a file name)
        Signal Proba Image
        argument: ``--outSignal_Proba %s``
outSignal2: (a boolean or a file name)
        Signal Mask Image
        argument: ``--outSignal_Mask %s``
outMasked: (a boolean or a file name)
        Masked T1 Map Image
        argument: ``--outMasked_T1_Map %s``
outMasked2: (a boolean or a file name)
        Masked Iso Image
        argument: ``--outMasked_T1weighted %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

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

JistLaminarProfileCalculator

Link to code

Wraps the executable 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:

[Optional]
inIntensity: (an existing file name)
        Intensity Profile Image
        argument: ``--inIntensity %s``
inMask: (an existing file name)
        Mask Image (opt, 3D or 4D)
        argument: ``--inMask %s``
incomputed: ('mean' or 'stdev' or 'skewness' or 'kurtosis')
        computed statistic
        argument: ``--incomputed %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outResult: (a boolean or a file name)
        Result
        argument: ``--outResult %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outResult: (an existing file name)
        Result

JistLaminarProfileGeometry

Link to code

Wraps the executable 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:

[Optional]
inProfile: (an existing file name)
        Profile Surface Image
        argument: ``--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
        argument: ``--incomputed %s``
inregularization: ('none' or 'Gaussian')
        regularization
        argument: ``--inregularization %s``
insmoothing: (a float)
        smoothing parameter
        argument: ``--insmoothing %f``
inoutside: (a float)
        outside extension (mm)
        argument: ``--inoutside %f``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outResult: (a boolean or a file name)
        Result
        argument: ``--outResult %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outResult: (an existing file name)
        Result

JistLaminarProfileSampling

Link to code

Wraps the executable 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:

[Optional]
inProfile: (an existing file name)
        Profile Surface Image
        argument: ``--inProfile %s``
inIntensity: (an existing file name)
        Intensity Image
        argument: ``--inIntensity %s``
inCortex: (an existing file name)
        Cortex Mask (opt)
        argument: ``--inCortex %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outProfilemapped: (a boolean or a file name)
        Profile-mapped Intensity Image
        argument: ``--outProfilemapped %s``
outProfile2: (a boolean or a file name)
        Profile 4D Mask
        argument: ``--outProfile2 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

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

JistLaminarROIAveraging

Link to code

Wraps the executable 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:

[Optional]
inIntensity: (an existing file name)
        Intensity Profile Image
        argument: ``--inIntensity %s``
inROI: (an existing file name)
        ROI Mask
        argument: ``--inROI %s``
inROI2: (a unicode string)
        ROI Name
        argument: ``--inROI2 %s``
inMask: (an existing file name)
        Mask Image (opt, 3D or 4D)
        argument: ``--inMask %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outROI3: (a boolean or a file name)
        ROI Average
        argument: ``--outROI3 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outROI3: (an existing file name)
        ROI Average

JistLaminarVolumetricLayering

Link to code

Wraps the executable 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:

[Optional]
inInner: (an existing file name)
        Inner Distance Image (GM/WM boundary)
        argument: ``--inInner %s``
inOuter: (an existing file name)
        Outer Distance Image (CSF/GM boundary)
        argument: ``--inOuter %s``
inNumber: (an integer (int or long))
        Number of layers
        argument: ``--inNumber %d``
inMax: (an integer (int or long))
        Max iterations for narrow band evolution
        argument: ``--inMax %d``
inMin: (a float)
        Min change ratio for narrow band evolution
        argument: ``--inMin %f``
inLayering: ('distance-preserving' or 'volume-preserving')
        Layering method
        argument: ``--inLayering %s``
inLayering2: ('outward' or 'inward')
        Layering direction
        argument: ``--inLayering2 %s``
incurvature: (an integer (int or long))
        curvature approximation scale (voxels)
        argument: ``--incurvature %d``
inratio: (a float)
        ratio smoothing kernel size (voxels)
        argument: ``--inratio %f``
inpresmooth: ('true' or 'false')
        pre-smooth cortical surfaces
        argument: ``--inpresmooth %s``
inTopology: ('26/6' or '6/26' or '18/6' or '6/18' or '6/6' or 'wcs'
          or 'wco' or 'no')
        Topology
        argument: ``--inTopology %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outContinuous: (a boolean or a file name)
        Continuous depth measurement
        argument: ``--outContinuous %s``
outDiscrete: (a boolean or a file name)
        Discrete sampled layers
        argument: ``--outDiscrete %s``
outLayer: (a boolean or a file name)
        Layer boundary surfaces
        argument: ``--outLayer %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

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 the executable 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:

[Optional]
inVolume: (an existing file name)
        Volume 1
        argument: ``--inVolume %s``
inVolume2: (an existing file name)
        Volume 2
        argument: ``--inVolume2 %s``
inOperation: ('Add' or 'Subtract' or 'Multiply' or 'Divide' or 'Min'
          or 'Max')
        Operation
        argument: ``--inOperation %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outResult: (a boolean or a file name)
        Result Volume
        argument: ``--outResult %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outResult: (an existing file name)
        Result Volume

MedicAlgorithmLesionToads

Link to code

Wraps the executable 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:

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

Outputs:

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

MedicAlgorithmMipavReorient

Link to code

Wraps the executable 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:

[Optional]
inSource: (a list of items which are a file name)
        Source
        argument: ``--inSource %s``
inTemplate: (an existing file name)
        Template
        argument: ``--inTemplate %s``
inNew: ('Dicom axial' or 'Dicom coronal' or 'Dicom sagittal' or 'User
          defined')
        New image orientation
        argument: ``--inNew %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)
        argument: ``--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)
        argument: ``--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)
        argument: ``--inUser3 %s``
inUser4: ('Axial' or 'Coronal' or 'Sagittal' or 'Unknown')
        User defined Image Orientation
        argument: ``--inUser4 %s``
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
        argument: ``--inInterpolation %s``
inResolution: ('Unchanged' or 'Finest cubic' or 'Coarsest cubic' or
          'Same as template')
        Resolution
        argument: ``--inResolution %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outReoriented: (a list of items which are a file name)
        Reoriented Volume
        argument: ``--outReoriented %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

None

MedicAlgorithmN3

Link to code

Wraps the executable 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:

[Optional]
inInput: (an existing file name)
        Input Volume
        argument: ``--inInput %s``
inSignal: (a float)
        Default = min + 1, Values at less than threshold are treated as part
        of the background
        argument: ``--inSignal %f``
inMaximum: (an integer (int or long))
        Maximum number of Iterations
        argument: ``--inMaximum %d``
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.
        argument: ``--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.
        argument: ``--inField %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.
        argument: ``--inSubsample %f``
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.
        argument: ``--inKernel %f``
inWeiner: (a float)
        Usually between 0.0-1.0
        argument: ``--inWeiner %f``
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.
        argument: ``--inAutomatic %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outInhomogeneity: (a boolean or a file name)
        Inhomogeneity Corrected Volume
        argument: ``--outInhomogeneity %s``
outInhomogeneity2: (a boolean or a file name)
        Inhomogeneity Field
        argument: ``--outInhomogeneity2 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

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

MedicAlgorithmSPECTRE2010

Link to code

Wraps the executable 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:

[Optional]
inInput: (an existing file name)
        Input volume to be skullstripped.
        argument: ``--inInput %s``
inAtlas: (an existing file name)
        SPECTRE atlas description file. A text file enumerating atlas files
        and landmarks.
        argument: ``--inAtlas %s``
inInitial: (an integer (int or long))
        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.
        argument: ``--inInitial %d``
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.
        argument: ``--inImage %s``
inOutput: ('true' or 'false')
        Determines if the output results are transformed back into the space
        of the original input image.
        argument: ``--inOutput %s``
inFind: ('true' or 'false')
        Find Midsaggital Plane
        argument: ``--inFind %s``
inRun: ('true' or 'false')
        Run Smooth Brain Mask
        argument: ``--inRun %s``
inResample: ('true' or 'false')
        Determines if the data is resampled to be isotropic during the
        processing.
        argument: ``--inResample %s``
inInitial2: (a float)
        Initial probability threshold
        argument: ``--inInitial2 %f``
inMinimum: (a float)
        Minimum probability threshold
        argument: ``--inMinimum %f``
inMMC: (an integer (int or long))
        The size of the dilation step within the Modified Morphological
        Closing.
        argument: ``--inMMC %d``
inMMC2: (an integer (int or long))
        The size of the erosion step within the Modified Morphological
        Closing.
        argument: ``--inMMC2 %d``
inInhomogeneity: ('true' or 'false')
        Set to false by default, this parameter will make FANTASM try to do
        inhomogeneity correction during it's iterative cycle.
        argument: ``--inInhomogeneity %s``
inSmoothing: (a float)
        argument: ``--inSmoothing %f``
inBackground: (a float)
        argument: ``--inBackground %f``
inOutput2: ('true' or 'false')
        Output Plane?
        argument: ``--inOutput2 %s``
inOutput3: ('true' or 'false')
        Output Split-Halves?
        argument: ``--inOutput3 %s``
inOutput4: ('true' or 'false')
        Output Segmentation on Plane?
        argument: ``--inOutput4 %s``
inDegrees: ('Rigid - 6' or 'Global rescale - 7' or 'Specific rescale
          - 9' or 'Affine - 12')
        Degrees of freedom
        argument: ``--inDegrees %s``
inCost: ('Correlation ratio' or 'Least squares' or 'Normalized cross
          correlation' or 'Normalized mutual information')
        Cost function
        argument: ``--inCost %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
        argument: ``--inRegistration %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
        argument: ``--inOutput5 %s``
inApply: ('All' or 'X' or 'Y' or 'Z')
        Apply rotation
        argument: ``--inApply %s``
inMinimum2: (a float)
        Minimum angle
        argument: ``--inMinimum2 %f``
inMaximum: (a float)
        Maximum angle
        argument: ``--inMaximum %f``
inCoarse: (a float)
        Coarse angle increment
        argument: ``--inCoarse %f``
inFine: (a float)
        Fine angle increment
        argument: ``--inFine %f``
inMultiple: (an integer (int or long))
        Multiple of tolerance to bracket the minimum
        argument: ``--inMultiple %d``
inNumber: (an integer (int or long))
        Number of iterations
        argument: ``--inNumber %d``
inNumber2: (an integer (int or long))
        Number of minima from Level 8 to test at Level 4
        argument: ``--inNumber2 %d``
inUse: ('true' or 'false')
        Use the max of the min resolutions of the two datasets when
        resampling
        argument: ``--inUse %s``
inSubsample: ('true' or 'false')
        Subsample image for speed
        argument: ``--inSubsample %s``
inSkip: ('true' or 'false')
        Skip multilevel search (Assume images are close to alignment)
        argument: ``--inSkip %s``
inMultithreading: ('true' or 'false')
        Set to false by default, this parameter controls the multithreaded
        behavior of the linear registration.
        argument: ``--inMultithreading %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %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.
        argument: ``--outOriginal %s``
outStripped: (a boolean or a file name)
        Skullstripped result of the input volume with just the brain.
        argument: ``--outStripped %s``
outMask: (a boolean or a file name)
        Binary Mask of the skullstripped result with just the brain
        argument: ``--outMask %s``
outPrior: (a boolean or a file name)
        Probability prior from the atlas registrations
        argument: ``--outPrior %s``
outFANTASM: (a boolean or a file name)
        Tissue classification of of the whole input volume.
        argument: ``--outFANTASM %s``
outd0: (a boolean or a file name)
        Initial Brainmask
        argument: ``--outd0 %s``
outMidsagittal: (a boolean or a file name)
        Plane dividing the brain hemispheres
        argument: ``--outMidsagittal %s``
outSplitHalves: (a boolean or a file name)
        Skullstripped mask of the brain with the hemispheres divided.
        argument: ``--outSplitHalves %s``
outSegmentation: (a boolean or a file name)
        2D image showing the tissue classification on the midsagittal plane
        argument: ``--outSegmentation %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

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.
outStripped: (an existing file name)
        Skullstripped result of the input volume with just the brain.
outMask: (an existing file name)
        Binary Mask of the skullstripped result with just the brain
outPrior: (an existing file name)
        Probability prior from the atlas registrations
outFANTASM: (an existing file name)
        Tissue classification of of the whole input volume.
outd0: (an existing file name)
        Initial Brainmask
outMidsagittal: (an existing file name)
        Plane dividing the brain hemispheres
outSplitHalves: (an existing file name)
        Skullstripped mask of the brain with the hemispheres divided.
outSegmentation: (an existing file name)
        2D image showing the tissue classification on the midsagittal plane

MedicAlgorithmThresholdToBinaryMask

Link to code

Wraps the executable 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:

[Optional]
inLabel: (a list of items which are a file name)
        Input volumes
        argument: ``--inLabel %s``
inMinimum: (a float)
        Minimum threshold value.
        argument: ``--inMinimum %f``
inMaximum: (a float)
        Maximum threshold value.
        argument: ``--inMaximum %f``
inUse: ('true' or 'false')
        Use the images max intensity as the max value of the range.
        argument: ``--inUse %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outBinary: (a list of items which are a file name)
        Binary Mask
        argument: ``--outBinary %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

None

RandomVol

Link to code

Wraps the executable 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:

[Optional]
inSize: (an integer (int or long))
        Size of Volume in X direction
        argument: ``--inSize %d``
inSize2: (an integer (int or long))
        Size of Volume in Y direction
        argument: ``--inSize2 %d``
inSize3: (an integer (int or long))
        Size of Volume in Z direction
        argument: ``--inSize3 %d``
inSize4: (an integer (int or long))
        Size of Volume in t direction
        argument: ``--inSize4 %d``
inStandard: (an integer (int or long))
        Standard Deviation for Normal Distribution
        argument: ``--inStandard %d``
inLambda: (a float)
        Lambda Value for Exponential Distribution
        argument: ``--inLambda %f``
inMaximum: (an integer (int or long))
        Maximum Value
        argument: ``--inMaximum %d``
inMinimum: (an integer (int or long))
        Minimum Value
        argument: ``--inMinimum %d``
inField: ('Uniform' or 'Normal' or 'Exponential')
        Field
        argument: ``--inField %s``
xPrefExt: ('nrrd')
        Output File Type
        argument: ``--xPrefExt %s``
outRand1: (a boolean or a file name)
        Rand1
        argument: ``--outRand1 %s``
null: (a unicode string)
        Execution Time
        argument: ``--null %s``
xDefaultMem: (an integer (int or long))
        Set default maximum heap size
        argument: ``-xDefaultMem %d``
xMaxProcess: (an integer (int or long), nipype default value: 1)
        Set default maximum number of processes.
        argument: ``-xMaxProcess %d``
args: (a unicode string)
        Additional parameters to the command
        argument: ``%s``
environ: (a dictionary with keys which are a bytes or None or a value
          of class 'str' and with values which are a bytes or None or a
          value of class 'str', nipype default value: {})
        Environment variables

Outputs:

outRand1: (an existing file name)
        Rand1