interfaces.semtools.registration.brainsfit¶

[Mandatory]

[Optional]
ROIAutoClosingSize: (a float)
        This flag is only relevant 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.
        flag: --ROIAutoClosingSize %f
ROIAutoDilateSize: (a float)
        This flag is only relevant when using ROIAUTO mode for initializing
        masks. It defines the final dilation size to capture a bit of
        background outside the tissue region. A setting of 10mm has been
        shown to help regularize a BSpline registration type so that there
        is some background constraints to match the edges of the head
        better.
        flag: --ROIAutoDilateSize %f
args: (a unicode string)
        Additional parameters to the command
        flag: %s
backgroundFillValue: (a float)
        This value will be used for filling those areas of the output image
        that have no corresponding voxels in the input moving image.
        flag: --backgroundFillValue %f
bsplineTransform: (a boolean or a file name)
        (optional) Output estimated transform - in case the computed
        transform is BSpline. NOTE: You must set at least one output object
        (transform and/or output volume).
        flag: --bsplineTransform %s
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.,
        flag: --costFunctionConvergenceFactor %f
costMetric: ('MMI' or 'MSE' or 'NC' or 'MIH')
        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)
        flag: --costMetric %s
debugLevel: (an integer (int or long))
        Display debug messages, and produce debug intermediate results.
        0=OFF, 1=Minimal, 10=Maximum debugging.
        flag: --debugLevel %d
environ: (a dictionary with keys which are a newbytes or None or a
         newstr or None and with values which are a newbytes or None or a
         newstr or None, nipype default value: {})
        Environment variables
failureExitCode: (an integer (int or long))
        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.
        flag: --failureExitCode %d
fixedBinaryVolume: (an existing file name)
        Fixed Image binary mask volume, required if Masking Option is ROI.
        Image areas where the mask volume has zero value are ignored during
        the registration.
        flag: --fixedBinaryVolume %s
fixedVolume: (an existing file name)
        Input fixed image (the moving image will be transformed into this
        image space).
        flag: --fixedVolume %s
fixedVolume2: (an existing file name)
        Input fixed image that will be used for multimodal registration.
        (the moving image will be transformed into this image space).
        flag: --fixedVolume2 %s
fixedVolumeTimeIndex: (an integer (int or long))
        The index in the time series for the 3D fixed image to fit. Only
        allowed if the fixed input volume is 4-dimensional.
        flag: --fixedVolumeTimeIndex %d
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.
        flag: --gui
histogramMatch: (a boolean)
        Apply histogram matching operation for the input images to make them
        more similar. This is suitable for images of the same modality that
        may have different brightness or contrast, but the same overall
        intensity profile. Do NOT use if registering images from different
        modalities.
        flag: --histogramMatch
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)
        Transform to be applied to the moving image to initialize the
        registration. This can only be used if Initialize Transform Mode is
        Off.
        flag: --initialTransform %s
initializeRegistrationByCurrentGenericTransform: (a boolean)
        If this flag is ON, the current generic composite transform,
        resulted from the linear registration stages, is set to initialize
        the follow nonlinear registration process. However, by the default
        behaviour, the moving image is first warped based on the existant
        transform before it is passed to the BSpline registration filter. It
        is done to speed up the BSpline registration by reducing the
        computations of composite transform Jacobian.
        flag: --initializeRegistrationByCurrentGenericTransform
initializeTransformMode: ('Off' or 'useMomentsAlign' or
         'useCenterOfHeadAlign' or 'useGeometryAlign' or
         'useCenterOfROIAlign')
        Determine how to initialize the transform center. useMomentsAlign
        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. useGeometryAlign
        on assumes that the center of the voxel lattice of the images
        represent similar structures. Off assumes that the physical space of
        the images are close. This flag is mutually exclusive with the
        Initialization transform.
        flag: --initializeTransformMode %s
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,
        Hamming, Cosine, Welch, Lanczos, 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.
        flag: --interpolationMode %s
linearTransform: (a boolean or a file name)
        (optional) Output estimated transform - in case the computed
        transform is not BSpline. NOTE: You must set at least one output
        object (transform and/or output volume).
        flag: --linearTransform %s
logFileReport: (a boolean or a file name)
        A file to write out final information report in CSV file: MetricName
        ,MetricValue,FixedImageName,FixedMaskName,MovingImageName,MovingMask
        Name
        flag: --logFileReport %s
maskInferiorCutOffFromCenter: (a float)
        If Initialize Transform Mode is set to useCenterOfHeadAlign or
        Masking Option is ROIAUTO then this value defines the how much is
        cut of from the inferior part of the image. The cut-off distance is
        specified in millimeters, relative to the image center. If the value
        is 1000 or larger then no cut-off performed.
        flag: --maskInferiorCutOffFromCenter %f
maskProcessingMode: ('NOMASK' or 'ROIAUTO' or 'ROI')
        Specifies a mask to only consider a certain image region for the
        registration. If ROIAUTO is chosen, then the mask is computed using
        Otsu thresholding and hole filling. If ROI is chosen then the mask
        has to be specified as in input.
        flag: --maskProcessingMode %s
maxBSplineDisplacement: (a float)
        Maximum allowed displacements in image physical coordinates (mm) 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.,
        flag: --maxBSplineDisplacement %f
maximumNumberOfCorrections: (an integer (int or long))
        Maximum number of corrections in lbfgsb optimizer.
        flag: --maximumNumberOfCorrections %d
maximumNumberOfEvaluations: (an integer (int or long))
        Maximum number of evaluations for line search in lbfgsb optimizer.
        flag: --maximumNumberOfEvaluations %d
maximumStepLength: (a float)
        Starting step length of the optimizer. In general, higher values
        allow for recovering larger initial misalignments but there is an
        increased chance that the registration will not converge.
        flag: --maximumStepLength %f
medianFilterSize: (a list of items which are an integer (int or
         long))
        Apply median filtering to reduce noise in the input volumes. The 3
        values specify the radius for the optional MedianImageFilter
        preprocessing in all 3 directions (in voxels).
        flag: --medianFilterSize %s
metricSamplingStrategy: ('Random')
        It defines the method that registration filter uses to sample the
        input fixed image. Only Random is supported for now.
        flag: --metricSamplingStrategy %s
minimumStepLength: (a list of items which are a float)
        Each step in the optimization takes steps at least this big. When
        none are possible, registration is complete. Smaller values allows
        the optimizer to make smaller adjustments, but the registration time
        may increase.
        flag: --minimumStepLength %s
movingBinaryVolume: (an existing file name)
        Moving Image binary mask volume, required if Masking Option is ROI.
        Image areas where the mask volume has zero value are ignored during
        the registration.
        flag: --movingBinaryVolume %s
movingVolume: (an existing file name)
        Input moving image (this image will be transformed into the fixed
        image space).
        flag: --movingVolume %s
movingVolume2: (an existing file name)
        Input moving image that will be used for multimodal
        registration(this image will be transformed into the fixed image
        space).
        flag: --movingVolume2 %s
movingVolumeTimeIndex: (an integer (int or long))
        The index in the time series for the 3D moving image to fit. Only
        allowed if the moving input volume is 4-dimensional
        flag: --movingVolumeTimeIndex %d
numberOfHistogramBins: (an integer (int or long))
        The number of histogram levels used for mutual information metric
        estimation.
        flag: --numberOfHistogramBins %d
numberOfIterations: (a list of items which are an integer (int or
         long))
        The maximum number of iterations to try before stopping the
        optimization. When using a lower value (500-1000) then the
        registration is forced to terminate earlier but there is a higher
        risk of stopping before an optimal solution is reached.
        flag: --numberOfIterations %s
numberOfMatchPoints: (an integer (int or long))
        Number of histogram match points used for mutual information metric
        estimation.
        flag: --numberOfMatchPoints %d
numberOfSamples: (an integer (int or long))
        The number of voxels sampled for mutual information computation.
        Increase this for higher accuracy, at the cost of longer computation
        time., NOTE that it is suggested to use samplingPercentage instead
        of this option. However, if set to non-zero, numberOfSamples
        overwrites the samplingPercentage option.
        flag: --numberOfSamples %d
numberOfThreads: (an integer (int or long))
        Explicitly specify the maximum number of threads to use. (default is
        auto-detected)
        flag: --numberOfThreads %d
outputFixedVolumeROI: (a boolean or a file name)
        ROI that is automatically computed from the fixed image. Only
        available if Masking Option is ROIAUTO. Image areas where the mask
        volume has zero value are ignored during the registration.
        flag: --outputFixedVolumeROI %s
outputMovingVolumeROI: (a boolean or a file name)
        ROI that is automatically computed from the moving image. Only
        available if Masking Option is ROIAUTO. Image areas where the mask
        volume has zero value are ignored during the registration.
        flag: --outputMovingVolumeROI %s
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.
        flag: --outputTransform %s
outputVolume: (a boolean or a file name)
        (optional) Output image: the moving image warped to the fixed image
        space. NOTE: You must set at least one output object (transform
        and/or output volume).
        flag: --outputVolume %s
outputVolumePixelType: ('float' or 'short' or 'ushort' or 'int' or
         'uint' or 'uchar')
        Data type for representing a voxel of the Output Volume.
        flag: --outputVolumePixelType %s
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.,
        flag: --projectedGradientTolerance %f
promptUser: (a boolean)
        Prompt the user to hit enter each time an image is sent to the
        DebugImageViewer
        flag: --promptUser
relaxationFactor: (a float)
        Specifies how quickly the optimization step length is decreased
        during registration. The value must be larger than 0 and smaller
        than 1. Larger values result in slower step size decrease, which
        allow for recovering larger initial misalignments but it increases
        the registration time and the chance that the registration will not
        converge.
        flag: --relaxationFactor %f
removeIntensityOutliers: (a float)
        Remove very high and very low intensity voxels from the input
        volumes. The parameter specifies 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 0.005%
        of both tails will be thrown away, so 0.01% of intensities in total
        would be ignored in the statistic calculation.
        flag: --removeIntensityOutliers %f
reproportionScale: (a float)
        ScaleVersor3D 'Scale' compensation factor. Increase this to allow
        for more rescaling in a ScaleVersor3D or ScaleSkewVersor3D search
        pattern. 1.0 works well with a translationScale of 1000.0
        flag: --reproportionScale %f
samplingPercentage: (a float)
        Fraction of voxels of the fixed image that will be used for
        registration. The number has to be larger than zero and less or
        equal to one. Higher values increase the computation time but may
        give more accurate results. You can also limit the sampling focus
        with ROI masks and ROIAUTO mask generation. The default is 0.002
        (use approximately 0.2% of voxels, resulting in 100000 samples in a
        512x512x192 volume) to provide a very fast registration in most
        cases. Typical values range from 0.01 (1%) for low detail images to
        0.2 (20%) for high detail images.
        flag: --samplingPercentage %f
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.
        flag: --scaleOutputValues
skewScale: (a float)
        ScaleSkewVersor3D Skew compensation factor. Increase this to allow
        for more skew in a ScaleSkewVersor3D search pattern. 1.0 works well
        with a translationScale of 1000.0
        flag: --skewScale %f
splineGridSize: (a list of items which are an integer (int or long))
        Number of BSpline grid subdivisions along each axis of the fixed
        image, centered on the image space. Values must be 3 or higher for
        the BSpline to be correctly computed.
        flag: --splineGridSize %s
strippedOutputTransform: (a boolean or a file name)
        Rigid component of the estimated affine transform. Can be used to
        rigidly register the moving image to the fixed image. NOTE: This
        value is overridden if either bsplineTransform or linearTransform is
        set.
        flag: --strippedOutputTransform %s
terminal_output: (u'stream' or u'allatonce' or u'file' or u'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
transformType: (a list of items which are a unicode string)
        Specifies a list of registration types to be used. The valid types
        are, Rigid, ScaleVersor3D, ScaleSkewVersor3D, Affine, BSpline and
        SyN. Specifying 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.
        flag: --transformType %s
translationScale: (a float)
        How much to scale up changes in position (in mm) compared to unit
        rotational changes (in radians) -- decrease this to allow for more
        rotation in the search pattern.
        flag: --translationScale %f
useAffine: (a boolean)
        Perform an Affine registration as part of the sequential
        registration steps. This family of options overrides the use of
        transformType if any of them are set.
        flag: --useAffine
useBSpline: (a boolean)
        Perform a BSpline registration as part of the sequential
        registration steps. This family of options overrides the use of
        transformType if any of them are set.
        flag: --useBSpline
useComposite: (a boolean)
        Perform a Composite registration as part of the sequential
        registration steps. This family of options overrides the use of
        transformType if any of them are set.
        flag: --useComposite
useROIBSpline: (a boolean)
        If enabled then the bounding box of the input ROIs defines the
        BSpline grid support region. Otherwise the BSpline grid support
        region is the whole fixed image.
        flag: --useROIBSpline
useRigid: (a boolean)
        Perform a rigid registration as part of the sequential registration
        steps. This family of options overrides the use of transformType if
        any of them are set.
        flag: --useRigid
useScaleSkewVersor3D: (a boolean)
        Perform a ScaleSkewVersor3D registration as part of the sequential
        registration steps. This family of options overrides the use of
        transformType if any of them are set.
        flag: --useScaleSkewVersor3D
useScaleVersor3D: (a boolean)
        Perform a ScaleVersor3D registration as part of the sequential
        registration steps. This family of options overrides the use of
        transformType if any of them are set.
        flag: --useScaleVersor3D
useSyN: (a boolean)
        Perform a SyN registration as part of the sequential registration
        steps. This family of options overrides the use of transformType if
        any of them are set.
        flag: --useSyN
writeOutputTransformInFloat: (a boolean)
        By default, the output registration transforms (either the output
        composite transform or each transform component) are written to the
        disk in double precision. If this flag is ON, the output transforms
        will be written in single (float) precision. It is especially
        important if the output transform is a displacement field transform,
        or it is a composite transform that includes several displacement
        fields.
        flag: --writeOutputTransformInFloat
writeTransformOnFailure: (a boolean)
        Flag to save the final transform even if the numberOfIterations are
        reached without convergence. (Intended for use when
        --failureExitCode 0 )
        flag: --writeTransformOnFailure

Release	Devel
0.13.0-rc1	0.13.0-rc1
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interfaces.semtools.registration.brainsfit¶

BRAINSFit¶