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interfaces.slicer.registration

BRAINSDemonWarp

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/slicer/registration.py#L280

Wraps command ** BRAINSDemonWarp **

title: Demon Registration (BRAINS)

category: Registration

description:
This program finds a deformation field to warp a moving image onto a fixed image. The images must be of the same signal kind, and contain an image of the same kind of object. This program uses the Thirion Demons warp software in ITK, the Insight Toolkit. Additional information is available at: http://www.nitrc.org/projects/brainsdemonwarp.

version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSDemonWarp

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

contributor: This tool was developed by Hans J. Johnson and Greg Harris.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs:

[Mandatory]

[Optional]
args: (a string)
        Additional parameters to the command
arrayOfPyramidLevelIterations: (an integer)
        The number of iterations for each pyramid level
backgroundFillValue: (an integer)
        Replacement value to overwrite background when performing BOBF
checkerboardPatternSubdivisions: (an integer)
        Number of Checkerboard subdivisions in all 3 directions
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
fixedBinaryVolume: (an existing file name)
        Mask filename for desired region of interest in the Fixed image.
fixedVolume: (an existing file name)
        Required: input fixed (target) image
gradient_type: ('0' or '1' or '2')
        Type of gradient used for computing the demons force (0 is symmetrized, 1 is fixed
        image, 2 is moving image)
gui: (a boolean)
        Display intermediate image volumes for debugging
histogramMatch: (a boolean)
        Histogram Match the input images.  This is suitable for images of the same modality that
        may have different absolute scales, but the same overall intensity profile.
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
initializeWithDeformationField: (an existing file name)
        Initial deformation field vector image file name
initializeWithTransform: (an existing file name)
        Initial Transform filename
inputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
        Input volumes will be typecast to this format: float|short|ushort|int|uchar
interpolationMode: ('NearestNeighbor' or 'Linear' or 'ResampleInPlace' or 'BSpline' or
         'WindowedSinc' or 'Hamming' or 'Cosine' or 'Welch' or 'Lanczos' or 'Blackman')
        Type of interpolation to be used when applying transform to moving volume.  Options are
        Linear, ResampleInPlace, NearestNeighbor, BSpline, or WindowedSinc
lowerThresholdForBOBF: (an integer)
        Lower threshold for performing BOBF
maskProcessingMode: ('NOMASK' or 'ROIAUTO' or 'ROI' or 'BOBF')
        What mode to use for using the masks: NOMASK|ROIAUTO|ROI|BOBF.  If ROIAUTO is choosen,
        then the mask is implicitly defined using a otsu forground and hole filling algorithm.
        Where the Region Of Interest mode uses the masks to define what parts of the image
        should be used for computing the deformation field.  Brain Only Background Fill uses the
        masks to pre-process the input images by clipping and filling in the background with a
        predefined value.
max_step_length: (a float)
        Maximum length of an update vector (0: no restriction)
medianFilterSize: (an integer)
        Median filter radius in all 3 directions.  When images have a lot of salt and pepper
        noise, this step can improve the registration.
minimumFixedPyramid: (an integer)
        The shrink factor for the first level of the fixed image pyramid. (i.e. start at 1/16
        scale, then 1/8, then 1/4, then 1/2, and finally full scale)
minimumMovingPyramid: (an integer)
        The shrink factor for the first level of the moving image pyramid. (i.e. start at 1/16
        scale, then 1/8, then 1/4, then 1/2, and finally full scale)
movingBinaryVolume: (an existing file name)
        Mask filename for desired region of interest in the Moving image.
movingVolume: (an existing file name)
        Required: input moving image
neighborhoodForBOBF: (an integer)
        neighborhood in all 3 directions to be included when performing BOBF
numberOfBCHApproximationTerms: (an integer)
        Number of terms in the BCH expansion
numberOfHistogramBins: (an integer)
        The number of histogram levels
numberOfMatchPoints: (an integer)
        The number of match points for histrogramMatch
numberOfPyramidLevels: (an integer)
        Number of image pyramid levels to use in the multi-resolution registration.
numberOfThreads: (an integer)
        Explicitly specify the maximum number of threads to use.
outputCheckerboardVolume: (a boolean or a file name)
        Genete a checkerboard image volume between the fixedVolume and the deformed
        movingVolume.
outputDebug: (a boolean)
        Flag to write debugging images after each step.
outputDeformationFieldVolume: (a boolean or a file name)
        Output deformation field vector image (will have the same physical space as the
        fixedVolume).
outputDisplacementFieldPrefix: (a string)
        Displacement field filename prefix for writing separate x, y, and z component images
outputNormalized: (a boolean)
        Flag to warp and write the normalized images to output.  In normalized images the image
        values are fit-scaled to be between 0 and the maximum storage type value.
outputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
        outputVolume will be typecast to this format: float|short|ushort|int|uchar
outputVolume: (a boolean or a file name)
        Required: output resampled moving image (will have the same physical space as the
        fixedVolume).
promptUser: (a boolean)
        Prompt the user to hit enter each time an image is sent to the DebugImageViewer
registrationFilterType: ('Demons' or 'FastSymmetricForces' or 'Diffeomorphic' or
         'LogDemons' or 'SymmetricLogDemons')
        Registration Filter Type:
        Demons|FastSymmetricForces|Diffeomorphic|LogDemons|SymmetricLogDemons
seedForBOBF: (an integer)
        coordinates in all 3 directions for Seed when performing BOBF
smoothDeformationFieldSigma: (a float)
        A gaussian smoothing value to be applied to the deformation feild at each iteration.
upFieldSmoothing: (a float)
        Smoothing sigma for the update field at each iteration
upperThresholdForBOBF: (an integer)
        Upper threshold for performing BOBF
use_vanilla_dem: (a boolean)
        Run vanilla demons algorithm

Outputs:

outputCheckerboardVolume: (an existing file name)
        Genete a checkerboard image volume between the fixedVolume and the deformed
        movingVolume.
outputDeformationFieldVolume: (an existing file name)
        Output deformation field vector image (will have the same physical space as the
        fixedVolume).
outputVolume: (an existing file name)
        Required: output resampled moving image (will have the same physical space as the
        fixedVolume).

BRAINSFit

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/slicer/registration.py#L206

Wraps command ** BRAINSFit **

title: General Registration (BRAINS)

category: Registration

description: Register a three-dimensional volume to a reference volume (Mattes Mutual Information by default). Full documentation avalable here: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.0/Modules/BRAINSFit. Method described in BRAINSFit: Mutual Information Registrations of Whole-Brain 3D Images, Using the Insight Toolkit, Johnson H.J., Harris G., Williams K., The Insight Journal, 2007. http://hdl.handle.net/1926/1291

version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSFit

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

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

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

Inputs:

[Mandatory]

[Optional]
NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_00: (a boolean)
        DO NOT USE THIS FLAG
NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_01: (a boolean)
        DO NOT USE THIS FLAG
NEVER_USE_THIS_FLAG_IT_IS_OUTDATED_02: (a boolean)
        DO NOT USE THIS FLAG
ROIAutoClosingSize: (a float)
        This flag is only relavent when using ROIAUTO mode for initializing masks.  It defines
        the hole closing size in mm.  It is rounded up to the nearest whole pixel size in each
        direction. The default is to use a closing size of 9mm.  For mouse data this value may
        need to be reset to 0.9 or smaller.
ROIAutoDilateSize: (a float)
        This flag is only relavent when using ROIAUTO mode for initializing masks.  It defines
        the final dilation size to capture a bit of background outside the tissue region.  At
        setting of 10mm has been shown to help regularize a BSpline registration type so that
        there is some background constraints to match the edges of the head better.
args: (a string)
        Additional parameters to the command
backgroundFillValue: (a float)
        Background fill value for output image.
bsplineTransform: (a boolean or a file name)
        (optional) Filename to which save the estimated transform. NOTE: You must set at least
        one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
        FINAL TRANSFORM IS BSpline
costFunctionConvergenceFactor: (a float)
         From itkLBFGSBOptimizer.h: Set/Get the CostFunctionConvergenceFactor. Algorithm
        terminates when the reduction in cost function is less than (factor * epsmcj) where
        epsmch is the machine precision. Typical values for factor: 1e+12 for low accuracy; 1e+7
        for moderate accuracy and 1e+1 for extremely high accuracy.  1e+9 seems to work well.,
costMetric: ('MMI' or 'MSE' or 'NC' or 'MC')
        The cost metric to be used during fitting. Defaults to MMI. Options are MMI (Mattes
        Mutual Information), MSE (Mean Square Error), NC (Normalized Correlation), MC (Match
        Cardinality for binary images)
debugLevel: (an integer)
        Display debug messages, and produce debug intermediate results.  0=OFF, 1=Minimal,
        10=Maximum debugging.
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
failureExitCode: (an integer)
        If the fit fails, exit with this status code.  (It can be used to force a successfult
        exit status of (0) if the registration fails due to reaching the maximum number of
        iterations.
fixedBinaryVolume: (an existing file name)
        Fixed Image binary mask volume, ONLY FOR MANUAL ROI mode.
fixedVolume: (an existing file name)
        The fixed image for registration by mutual information optimization.
fixedVolumeTimeIndex: (an integer)
        The index in the time series for the 3D fixed image to fit, if 4-dimensional.
forceMINumberOfThreads: (an integer)
        Force the the maximum number of threads to use for non thread safe MI metric.
gui: (a boolean)
        Display intermediate image volumes for debugging.  NOTE:  This is not part of the
        standard build sytem, and probably does nothing on your installation.
histogramMatch: (a boolean)
        Histogram Match the input images.  This is suitable for images of the same modality that
        may have different absolute scales, but the same overall intensity profile. Do NOT use
        if registering images from different modailties.
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
initialTransform: (an existing file name)
        Filename of transform used to initialize the registration.  This CAN NOT be used with
        either CenterOfHeadLAlign, MomentsAlign, GeometryAlign, or initialTransform file.
initializeTransformMode: ('Off' or 'useMomentsAlign' or 'useCenterOfHeadAlign' or
         'useGeometryAlign' or 'useCenterOfROIAlign')
        Determine how to initialize the transform center.  GeometryAlign on assumes that the
        center of the voxel lattice of the images represent similar structures.  MomentsAlign
        assumes that the center of mass of the images represent similar structures.
        useCenterOfHeadAlign attempts to use the top of head and shape of neck to drive a center
        of mass estimate.  Off assumes that the physical space of the images are close, and that
        centering in terms of the image Origins is a good starting point.  This flag is mutually
        exclusive with the initialTransform flag.
interpolationMode: ('NearestNeighbor' or 'Linear' or 'ResampleInPlace' or 'BSpline' or
         'WindowedSinc' or 'Hamming' or 'Cosine' or 'Welch' or 'Lanczos' or 'Blackman')
        Type of interpolation to be used when applying transform to moving volume.  Options are
        Linear, NearestNeighbor, BSpline, WindowedSinc, or ResampleInPlace.  The ResampleInPlace
        option will create an image with the same discrete voxel values and will adjust the
        origin and direction of the physical space interpretation.
linearTransform: (a boolean or a file name)
        (optional) Filename to which save the estimated transform. NOTE: You must set at least
        one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
        FINAL TRANSFORM IS ---NOT--- BSpline
maskInferiorCutOffFromCenter: (a float)
        For use with --useCenterOfHeadAlign (and --maskProcessingMode ROIAUTO): the cut-off
        below the image centers, in millimeters,
maskProcessingMode: ('NOMASK' or 'ROIAUTO' or 'ROI')
        What mode to use for using the masks.  If ROIAUTO is choosen, then the mask is
        implicitly defined using a otsu forground and hole filling algorithm. The Region Of
        Interest mode (choose ROI) uses the masks to define what parts of the image should be
        used for computing the transform.
maxBSplineDisplacement: (a float)
         Sets the maximum allowed displacements in image physical coordinates for BSpline
        control grid along each axis.  A value of 0.0 indicates that the problem should be
        unbounded.  NOTE:  This only constrains the BSpline portion, and does not limit the
        displacement from the associated bulk transform.  This can lead to a substantial
        reduction in computation time in the BSpline optimizer.,
maximumStepLength: (a float)
        Internal debugging parameter, and should probably never be used from the command line.
        This will be removed in the future.
medianFilterSize: (an integer)
        The radius for the optional MedianImageFilter preprocessing in all 3 directions.
minimumStepLength: (a float)
        Each step in the optimization takes steps at least this big.  When none are possible,
        registration is complete.
movingBinaryVolume: (an existing file name)
        Moving Image binary mask volume, ONLY FOR MANUAL ROI mode.
movingVolume: (an existing file name)
        The moving image for registration by mutual information optimization.
movingVolumeTimeIndex: (an integer)
        The index in the time series for the 3D moving image to fit, if 4-dimensional.
numberOfHistogramBins: (an integer)
        The number of histogram levels
numberOfIterations: (an integer)
        The maximum number of iterations to try before failing to converge.  Use an explicit
        limit like 500 or 1000 to manage risk of divergence
numberOfMatchPoints: (an integer)
        the number of match points
numberOfSamples: (an integer)
        The number of voxels sampled for mutual information computation.  Increase this for a
        slower, more careful fit.  You can also limit the sampling focus with ROI masks and
        ROIAUTO mask generation.
numberOfThreads: (an integer)
        Explicitly specify the maximum number of threads to use. (default is auto-detected)
outputFixedVolumeROI: (a boolean or a file name)
        The ROI automatically found in fixed image, ONLY FOR ROIAUTO mode.
outputMovingVolumeROI: (a boolean or a file name)
        The ROI automatically found in moving image, ONLY FOR ROIAUTO mode.
outputTransform: (a boolean or a file name)
        (optional) Filename to which save the (optional) estimated transform. NOTE: You must
        select either the outputTransform or the outputVolume option.
outputVolume: (a boolean or a file name)
        (optional) Output image for registration. NOTE: You must select either the
        outputTransform or the outputVolume option.
outputVolumePixelType: ('float' or 'short' or 'ushort' or 'int' or 'uint' or 'uchar')
        The output image Pixel Type is the scalar datatype for representation of the Output
        Volume.
permitParameterVariation: (an integer)
        A bit vector to permit linear transform parameters to vary under optimization.  The
        vector order corresponds with transform parameters, and beyond the end ones fill in as a
        default.  For instance, you can choose to rotate only in x (pitch) with 1,0,0;  this is
        mostly for expert use in turning on and off individual degrees of freedom in rotation,
        translation or scaling without multiplying the number of transform representations; this
        trick is probably meaningless when tried with the general affine transform.
projectedGradientTolerance: (a float)
         From itkLBFGSBOptimizer.h: Set/Get the ProjectedGradientTolerance. Algorithm terminates
        when the project gradient is below the tolerance. Default lbfgsb value is 1e-5, but 1e-4
        seems to work well.,
promptUser: (a boolean)
        Prompt the user to hit enter each time an image is sent to the DebugImageViewer
relaxationFactor: (a float)
        Internal debugging parameter, and should probably never be used from the command line.
        This will be removed in the future.
removeIntensityOutliers: (a float)
        The half percentage to decide outliers of image intensities. The default value is zero,
        which means no outlier removal. If the value of 0.005 is given, the moduel will throw
        away 0.005 % of both tails, so 0.01% of intensities in total would be ignored in its
        statistic calculation.
reproportionScale: (a float)
        ScaleVersor3D 'Scale' compensation factor.  Increase this to put more rescaling in a
        ScaleVersor3D or ScaleSkewVersor3D search pattern.  1.0 works well with a
        translationScale of 1000.0
scaleOutputValues: (a boolean)
        If true, and the voxel values do not fit within the minimum and maximum values of the
        desired outputVolumePixelType, then linearly scale the min/max output image voxel values
        to fit within the min/max range of the outputVolumePixelType.
skewScale: (a float)
        ScaleSkewVersor3D Skew compensation factor.  Increase this to put more skew in a
        ScaleSkewVersor3D search pattern.  1.0 works well with a translationScale of 1000.0
splineGridSize: (an integer)
        The number of subdivisions of the BSpline Grid to be centered on the image space.  Each
        dimension must have at least 3 subdivisions for the BSpline to be correctly computed.
strippedOutputTransform: (a boolean or a file name)
        File name for the rigid component of the estimated affine transform. Can be used to
        rigidly register the moving image to the fixed image. NOTE:  This value is overwritten
        if either bsplineTransform or linearTransform is set.
transformType: (a string)
        Specifies a list of registration types to be used.  The valid types are, Rigid,
        ScaleVersor3D, ScaleSkewVersor3D, Affine, and BSpline.  Specifiying more than one in a
        comma separated list will initialize the next stage with the previous results. If
        registrationClass flag is used, it overrides this parameter setting.
translationScale: (a float)
        How much to scale up changes in position compared to unit rotational changes in radians
        -- decrease this to put more rotation in the search pattern.
useAffine: (a boolean)
        Perform an Affine registration as part of the sequential registration steps.  This
        family of options superceeds the use of transformType if any of them are set.
useBSpline: (a boolean)
        Perform a BSpline registration as part of the sequential registration steps.  This
        family of options superceeds the use of transformType if any of them are set.
useCachingOfBSplineWeightsMode: ('ON' or 'OFF')
        This is a 5x speed advantage at the expense of requiring much more memory.  Only
        relevant when transformType is BSpline.
useComposite: (a boolean)
        Perform a Composite registration as part of the sequential registration steps.  This
        family of options superceeds the use of transformType if any of them are set.
useExplicitPDFDerivativesMode: ('AUTO' or 'ON' or 'OFF')
        Using mode AUTO means OFF for BSplineDeformableTransforms and ON for the linear
        transforms.  The ON alternative uses more memory to sometimes do a better job.
useRigid: (a boolean)
        Perform a rigid registration as part of the sequential registration steps.  This family
        of options superceeds the use of transformType if any of them are set.
useScaleSkewVersor3D: (a boolean)
        Perform a ScaleSkewVersor3D registration as part of the sequential registration steps.
        This family of options superceeds the use of transformType if any of them are set.
useScaleVersor3D: (a boolean)
        Perform a ScaleVersor3D registration as part of the sequential registration steps.  This
        family of options superceeds the use of transformType if any of them are set.
writeTransformOnFailure: (a boolean)
        Flag to save the final transform even if the numberOfIterations are reached without
        convergence. (Intended for use when --failureExitCode 0 )

Outputs:

bsplineTransform: (an existing file name)
        (optional) Filename to which save the estimated transform. NOTE: You must set at least
        one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
        FINAL TRANSFORM IS BSpline
linearTransform: (an existing file name)
        (optional) Filename to which save the estimated transform. NOTE: You must set at least
        one output object (either a deformed image or a transform.  NOTE: USE THIS ONLY IF THE
        FINAL TRANSFORM IS ---NOT--- BSpline
outputFixedVolumeROI: (an existing file name)
        The ROI automatically found in fixed image, ONLY FOR ROIAUTO mode.
outputMovingVolumeROI: (an existing file name)
        The ROI automatically found in moving image, ONLY FOR ROIAUTO mode.
outputTransform: (an existing file name)
        (optional) Filename to which save the (optional) estimated transform. NOTE: You must
        select either the outputTransform or the outputVolume option.
outputVolume: (an existing file name)
        (optional) Output image for registration. NOTE: You must select either the
        outputTransform or the outputVolume option.
strippedOutputTransform: (an existing file name)
        File name for the rigid component of the estimated affine transform. Can be used to
        rigidly register the moving image to the fixed image. NOTE:  This value is overwritten
        if either bsplineTransform or linearTransform is set.

BRAINSResample

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/slicer/registration.py#L27

Wraps command ** BRAINSResample **

title: Resample Image (BRAINS)

category: Registration

description:
This program collects together three common image processing tasks that all involve resampling an image volume: Resampling to a new resolution and spacing, applying a transformation (using an ITK transform IO mechanisms) and Warping (using a vector image deformation field). Full documentation available here: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.0/Modules/BRAINSResample.

version: 3.0.0

documentation-url: http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSResample

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

contributor: This tool was developed by Vincent Magnotta, Greg Harris, and Hans Johnson.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs:

[Mandatory]

[Optional]
args: (a string)
        Additional parameters to the command
defaultValue: (a float)
        Default voxel value
deformationVolume: (an existing file name)
        Displacement Field to be used to warp the image
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
gridSpacing: (an integer)
        Add warped grid to output image to help show the deformation that occured with specified
        spacing.   A spacing of 0 in a dimension indicates that grid lines should be rendered to
        fall exactly (i.e. do not allow displacements off that plane).  This is useful for
        makeing a 2D image of grid lines from the 3D space
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
inputVolume: (an existing file name)
        Image To Warp
interpolationMode: ('NearestNeighbor' or 'Linear' or 'ResampleInPlace' or 'BSpline' or
         'WindowedSinc' or 'Hamming' or 'Cosine' or 'Welch' or 'Lanczos' or 'Blackman')
        Type of interpolation to be used when applying transform to moving volume.  Options are
        Linear, ResampleInPlace, NearestNeighbor, BSpline, or WindowedSinc
inverseTransform: (a boolean)
        True/False is to compute inverse of given transformation. Default is false
numberOfThreads: (an integer)
        Explicitly specify the maximum number of threads to use.
outputVolume: (a boolean or a file name)
        Resulting deformed image
pixelType: ('float' or 'short' or 'ushort' or 'int' or 'uint' or 'uchar' or 'binary')
        Specifies the pixel type for the input/output images.  The "binary" pixel type uses a
        modified algorithm whereby the image is read in as unsigned char, a signed distance map
        is created, signed distance map is resampled, and then a thresholded image of type
        unsigned char is written to disk.
referenceVolume: (an existing file name)
        Reference image used only to define the output space. If not specified, the warping is
        done in the same space as the image to warp.
warpTransform: (an existing file name)
        Filename for the BRAINSFit transform used in place of the deformation field

Outputs:

outputVolume: (an existing file name)
        Resulting deformed image

VBRAINSDemonWarp

Code: file:///build/buildd/nipype-0.6.0/nipype/interfaces/slicer/registration.py#L104

Wraps command ** VBRAINSDemonWarp **

title: Vector Demon Registration (BRAINS)

category: Registration

description:
This program finds a deformation field to warp a moving image onto a fixed image. The images must be of the same signal kind, and contain an image of the same kind of object. This program uses the Thirion Demons warp software in ITK, the Insight Toolkit. Additional information is available at: http://www.nitrc.org/projects/brainsdemonwarp.

version: 3.0.0

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Modules:BRAINSDemonWarp

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

contributor: This tool was developed by Hans J. Johnson and Greg Harris.

acknowledgements: The development of this tool was supported by funding from grants NS050568 and NS40068 from the National Institute of Neurological Disorders and Stroke and grants MH31593, MH40856, from the National Institute of Mental Health.

Inputs:

[Mandatory]

[Optional]
args: (a string)
        Additional parameters to the command
arrayOfPyramidLevelIterations: (an integer)
        The number of iterations for each pyramid level
backgroundFillValue: (an integer)
        Replacement value to overwrite background when performing BOBF
checkerboardPatternSubdivisions: (an integer)
        Number of Checkerboard subdivisions in all 3 directions
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
fixedBinaryVolume: (an existing file name)
        Mask filename for desired region of interest in the Fixed image.
fixedVolume: (an existing file name)
        Required: input fixed (target) image
gradient_type: ('0' or '1' or '2')
        Type of gradient used for computing the demons force (0 is symmetrized, 1 is fixed
        image, 2 is moving image)
gui: (a boolean)
        Display intermediate image volumes for debugging
histogramMatch: (a boolean)
        Histogram Match the input images.  This is suitable for images of the same modality that
        may have different absolute scales, but the same overall intensity profile.
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the interface fails to
        run
initializeWithDeformationField: (an existing file name)
        Initial deformation field vector image file name
initializeWithTransform: (an existing file name)
        Initial Transform filename
inputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
        Input volumes will be typecast to this format: float|short|ushort|int|uchar
interpolationMode: ('NearestNeighbor' or 'Linear' or 'ResampleInPlace' or 'BSpline' or
         'WindowedSinc' or 'Hamming' or 'Cosine' or 'Welch' or 'Lanczos' or 'Blackman')
        Type of interpolation to be used when applying transform to moving volume.  Options are
        Linear, ResampleInPlace, NearestNeighbor, BSpline, or WindowedSinc
lowerThresholdForBOBF: (an integer)
        Lower threshold for performing BOBF
makeBOBF: (a boolean)
        Flag to make Brain-Only Background-Filled versions of the input and target volumes.
max_step_length: (a float)
        Maximum length of an update vector (0: no restriction)
medianFilterSize: (an integer)
        Median filter radius in all 3 directions.  When images have a lot of salt and pepper
        noise, this step can improve the registration.
minimumFixedPyramid: (an integer)
        The shrink factor for the first level of the fixed image pyramid. (i.e. start at 1/16
        scale, then 1/8, then 1/4, then 1/2, and finally full scale)
minimumMovingPyramid: (an integer)
        The shrink factor for the first level of the moving image pyramid. (i.e. start at 1/16
        scale, then 1/8, then 1/4, then 1/2, and finally full scale)
movingBinaryVolume: (an existing file name)
        Mask filename for desired region of interest in the Moving image.
movingVolume: (an existing file name)
        Required: input moving image
neighborhoodForBOBF: (an integer)
        neighborhood in all 3 directions to be included when performing BOBF
numberOfBCHApproximationTerms: (an integer)
        Number of terms in the BCH expansion
numberOfHistogramBins: (an integer)
        The number of histogram levels
numberOfMatchPoints: (an integer)
        The number of match points for histrogramMatch
numberOfPyramidLevels: (an integer)
        Number of image pyramid levels to use in the multi-resolution registration.
numberOfThreads: (an integer)
        Explicitly specify the maximum number of threads to use.
outputCheckerboardVolume: (a boolean or a file name)
        Genete a checkerboard image volume between the fixedVolume and the deformed
        movingVolume.
outputDebug: (a boolean)
        Flag to write debugging images after each step.
outputDeformationFieldVolume: (a boolean or a file name)
        Output deformation field vector image (will have the same physical space as the
        fixedVolume).
outputDisplacementFieldPrefix: (a string)
        Displacement field filename prefix for writing separate x, y, and z component images
outputNormalized: (a boolean)
        Flag to warp and write the normalized images to output.  In normalized images the image
        values are fit-scaled to be between 0 and the maximum storage type value.
outputPixelType: ('float' or 'short' or 'ushort' or 'int' or 'uchar')
        outputVolume will be typecast to this format: float|short|ushort|int|uchar
outputVolume: (a boolean or a file name)
        Required: output resampled moving image (will have the same physical space as the
        fixedVolume).
promptUser: (a boolean)
        Prompt the user to hit enter each time an image is sent to the DebugImageViewer
registrationFilterType: ('Demons' or 'FastSymmetricForces' or 'Diffeomorphic' or
         'LogDemons' or 'SymmetricLogDemons')
        Registration Filter Type:
        Demons|FastSymmetricForces|Diffeomorphic|LogDemons|SymmetricLogDemons
seedForBOBF: (an integer)
        coordinates in all 3 directions for Seed when performing BOBF
smoothDeformationFieldSigma: (a float)
        A gaussian smoothing value to be applied to the deformation feild at each iteration.
upFieldSmoothing: (a float)
        Smoothing sigma for the update field at each iteration
upperThresholdForBOBF: (an integer)
        Upper threshold for performing BOBF
use_vanilla_dem: (a boolean)
        Run vanilla demons algorithm
weightFactors: (a float)
        Weight fatctors for each input images

Outputs:

outputCheckerboardVolume: (an existing file name)
        Genete a checkerboard image volume between the fixedVolume and the deformed
        movingVolume.
outputDeformationFieldVolume: (an existing file name)
        Output deformation field vector image (will have the same physical space as the
        fixedVolume).
outputVolume: (an existing file name)
        Required: output resampled moving image (will have the same physical space as the
        fixedVolume).