.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.slicer.legacy.registration
=====================================


.. _nipype.interfaces.slicer.legacy.registration.AffineRegistration:


.. index:: AffineRegistration

AffineRegistration
------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L176>`__

Wraps the executable command ``AffineRegistration ``.

title: Affine Registration

category: Legacy.Registration

description: Registers two images together using an affine transform and mutual information. This module is often used to align images of different subjects or images of the same subject from different modalities.

This module can smooth images prior to registration to mitigate noise and improve convergence. Many of the registration parameters require a working knowledge of the algorithm although the default parameters are sufficient for many registration tasks.



version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration

contributor: Daniel Blezek (GE)

acknowledgements: This module was developed by Daniel Blezek while at GE Research with contributions from Jim Miller.

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        initialtransform: (an existing file name)
                Initial transform for aligning the fixed and moving image. Maps
                positions in the fixed coordinate frame to positions in the moving
                coordinate frame. Optional.
                argument: ``--initialtransform %s``
        fixedsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to fixed image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--fixedsmoothingfactor %d``
        translationscale: (a float)
                Relative scale of translations to rotations, i.e. a value of 100
                means 10mm = 1 degree. (Actual scale used is
                1/(TranslationScale^2)). This parameter is used to 'weight' or
                'standardized' the transform parameters and their effect on the
                registration objective function.
                argument: ``--translationscale %f``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        outputtransform: (a boolean or a file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
                argument: ``--outputtransform %s``
        spatialsamples: (an integer (int or long))
                Number of spatial samples to use in estimating Mattes Mutual
                Information. Larger values yield more accurate PDFs and improved
                registration quality.
                argument: ``--spatialsamples %d``
        histogrambins: (an integer (int or long))
                Number of histogram bins to use for Mattes Mutual Information.
                Reduce the number of bins if a registration fails. If the number of
                bins is too large, the estimated PDFs will be a field of impulses
                and will inhibit reliable registration estimation.
                argument: ``--histogrambins %d``
        movingsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to moving image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--movingsmoothingfactor %d``
        MovingImageFileName: (an existing file name)
                Moving image
                argument: ``%s``, position: -1
        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
        resampledmovingfilename: (a boolean or a file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
                argument: ``--resampledmovingfilename %s``
        iterations: (an integer (int or long))
                Number of iterations
                argument: ``--iterations %d``
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
                argument: ``%s``, position: -2

Outputs::

        resampledmovingfilename: (an existing file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
        outputtransform: (an existing file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).

.. _nipype.interfaces.slicer.legacy.registration.BSplineDeformableRegistration:


.. index:: BSplineDeformableRegistration

BSplineDeformableRegistration
-----------------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L87>`__

Wraps the executable command ``BSplineDeformableRegistration ``.

title: BSpline Deformable Registration

category: Legacy.Registration

description: Registers two images together using BSpline transform and mutual information.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BSplineDeformableRegistration

contributor: Bill Lorensen (GE)

acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        initialtransform: (an existing file name)
                Initial transform for aligning the fixed and moving image. Maps
                positions in the fixed coordinate frame to positions in the moving
                coordinate frame. This transform should be an affine or rigid
                transform. It is used an a bulk transform for the BSpline. Optional.
                argument: ``--initialtransform %s``
        maximumDeformation: (a float)
                If Constrain Deformation is checked, limit the deformation to this
                amount.
                argument: ``--maximumDeformation %f``
        gridSize: (an integer (int or long))
                Number of grid points on interior of the fixed image. Larger grid
                sizes allow for finer registrations.
                argument: ``--gridSize %d``
        MovingImageFileName: (an existing file name)
                Moving image
                argument: ``%s``, position: -1
        default: (an integer (int or long))
                Default pixel value used if resampling a pixel outside of the
                volume.
                argument: ``--default %d``
        histogrambins: (an integer (int or long))
                Number of histogram bins to use for Mattes Mutual Information.
                Reduce the number of bins if a deformable registration fails. If the
                number of bins is too large, the estimated PDFs will be a field of
                impulses and will inhibit reliable registration estimation.
                argument: ``--histogrambins %d``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        outputtransform: (a boolean or a file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions from the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
                argument: ``--outputtransform %s``
        spatialsamples: (an integer (int or long))
                Number of spatial samples to use in estimating Mattes Mutual
                Information. Larger values yield more accurate PDFs and improved
                registration quality.
                argument: ``--spatialsamples %d``
        resampledmovingfilename: (a boolean or a file name)
                Resampled moving image to fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
                argument: ``--resampledmovingfilename %s``
        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
        iterations: (an integer (int or long))
                Number of iterations
                argument: ``--iterations %d``
        outputwarp: (a boolean or a file name)
                Vector field that applies an equivalent warp as the BSpline. Maps
                positions from the fixed coordinate frame to the moving coordinate
                frame. Optional.
                argument: ``--outputwarp %s``
        constrain: (a boolean)
                Constrain the deformation to the amount specified in Maximum
                Deformation
                argument: ``--constrain ``
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
                argument: ``%s``, position: -2

Outputs::

        resampledmovingfilename: (an existing file name)
                Resampled moving image to fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
        outputtransform: (an existing file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions from the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
        outputwarp: (an existing file name)
                Vector field that applies an equivalent warp as the BSpline. Maps
                positions from the fixed coordinate frame to the moving coordinate
                frame. Optional.

.. _nipype.interfaces.slicer.legacy.registration.ExpertAutomatedRegistration:


.. index:: ExpertAutomatedRegistration

ExpertAutomatedRegistration
---------------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L632>`__

Wraps the executable command ``ExpertAutomatedRegistration ``.

title: Expert Automated Registration

category: Legacy.Registration

description: Provides rigid, affine, and BSpline registration methods via a simple GUI

version: 0.1.0.$Revision: 2104 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration

contributor: Stephen R Aylward (Kitware), Casey B Goodlett (Kitware)

acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        metric: ('MattesMI' or 'NormCorr' or 'MeanSqrd')
                Method to quantify image match
                argument: ``--metric %s``
        bsplineSamplingRatio: (a float)
                Portion of the image to use in computing the metric during BSpline
                registration
                argument: ``--bsplineSamplingRatio %f``
        movingLandmarks: (a list of items which are a list of from 3 to 3
                  items which are a float)
                Ordered list of landmarks in the moving image
                argument: ``--movingLandmarks %s...``
        expectedRotation: (a float)
                Expected misalignment after initialization
                argument: ``--expectedRotation %f``
        registration: ('None' or 'Initial' or 'Rigid' or 'Affine' or
                  'BSpline' or 'PipelineRigid' or 'PipelineAffine' or
                  'PipelineBSpline')
                Method for the registration process
                argument: ``--registration %s``
        fixedLandmarks: (a list of items which are a list of from 3 to 3
                  items which are a float)
                Ordered list of landmarks in the fixed image
                argument: ``--fixedLandmarks %s...``
        affineMaxIterations: (an integer (int or long))
                Maximum number of affine optimization iterations
                argument: ``--affineMaxIterations %d``
        fixedImage: (an existing file name)
                Image which defines the space into which the moving image is
                registered
                argument: ``%s``, position: -2
        rigidMaxIterations: (an integer (int or long))
                Maximum number of rigid optimization iterations
                argument: ``--rigidMaxIterations %d``
        expectedOffset: (a float)
                Expected misalignment after initialization
                argument: ``--expectedOffset %f``
        affineSamplingRatio: (a float)
                Portion of the image to use in computing the metric during affine
                registration
                argument: ``--affineSamplingRatio %f``
        expectedScale: (a float)
                Expected misalignment after initialization
                argument: ``--expectedScale %f``
        interpolation: ('NearestNeighbor' or 'Linear' or 'BSpline')
                Method for interpolation within the optimization process
                argument: ``--interpolation %s``
        sampleFromOverlap: (a boolean)
                Limit metric evaluation to the fixed image region overlapped by the
                moving image
                argument: ``--sampleFromOverlap ``
        controlPointSpacing: (an integer (int or long))
                Number of pixels between control points
                argument: ``--controlPointSpacing %d``
        initialization: ('None' or 'Landmarks' or 'ImageCenters' or
                  'CentersOfMass' or 'SecondMoments')
                Method to prime the registration process
                argument: ``--initialization %s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        numberOfThreads: (an integer (int or long))
                Number of CPU threads to use
                argument: ``--numberOfThreads %d``
        rigidSamplingRatio: (a float)
                Portion of the image to use in computing the metric during rigid
                registration
                argument: ``--rigidSamplingRatio %f``
        randomNumberSeed: (an integer (int or long))
                Seed to generate a consistent random number sequence
                argument: ``--randomNumberSeed %d``
        resampledImage: (a boolean or a file name)
                Registration results
                argument: ``--resampledImage %s``
        loadTransform: (an existing file name)
                Load a transform that is immediately applied to the moving image
                argument: ``--loadTransform %s``
        fixedImageMask: (an existing file name)
                Image which defines a mask for the fixed image
                argument: ``--fixedImageMask %s``
        saveTransform: (a boolean or a file name)
                Save the transform that results from registration
                argument: ``--saveTransform %s``
        movingImage: (an existing file name)
                The transform goes from the fixed image's space into the moving
                image's space
                argument: ``%s``, position: -1
        bsplineMaxIterations: (an integer (int or long))
                Maximum number of bspline optimization iterations
                argument: ``--bsplineMaxIterations %d``
        expectedSkew: (a float)
                Expected misalignment after initialization
                argument: ``--expectedSkew %f``
        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
        verbosityLevel: ('Silent' or 'Standard' or 'Verbose')
                Level of detail of reporting progress
                argument: ``--verbosityLevel %s``
        minimizeMemory: (a boolean)
                Reduce the amount of memory required at the cost of increased
                computation time
                argument: ``--minimizeMemory ``

Outputs::

        resampledImage: (an existing file name)
                Registration results
        saveTransform: (an existing file name)
                Save the transform that results from registration

.. _nipype.interfaces.slicer.legacy.registration.LinearRegistration:


.. index:: LinearRegistration

LinearRegistration
------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L471>`__

Wraps the executable command ``LinearRegistration ``.

title: Linear Registration

category: Legacy.Registration

description: Registers two images together using a rigid transform and mutual information.

version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/LinearRegistration

contributor: Daniel Blezek (GE)

acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        initialtransform: (an existing file name)
                Initial transform for aligning the fixed and moving image. Maps
                positions in the fixed coordinate frame to positions in the moving
                coordinate frame. Optional.
                argument: ``--initialtransform %s``
        histogrambins: (an integer (int or long))
                Number of histogram bins to use for Mattes Mutual Information.
                Reduce the number of bins if a registration fails. If the number of
                bins is too large, the estimated PDFs will be a field of impulses
                and will inhibit reliable registration estimation.
                argument: ``--histogrambins %d``
        translationscale: (a float)
                Relative scale of translations to rotations, i.e. a value of 100
                means 10mm = 1 degree. (Actual scale used 1/(TranslationScale^2)).
                This parameter is used to 'weight' or 'standardized' the transform
                parameters and their effect on the registration objective function.
                argument: ``--translationscale %f``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        outputtransform: (a boolean or a file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
                argument: ``--outputtransform %s``
        spatialsamples: (an integer (int or long))
                Number of spatial samples to use in estimating Mattes Mutual
                Information. Larger values yield more accurate PDFs and improved
                registration quality.
                argument: ``--spatialsamples %d``
        resampledmovingfilename: (a boolean or a file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
                argument: ``--resampledmovingfilename %s``
        movingsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to moving image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--movingsmoothingfactor %d``
        MovingImageFileName: (an existing file name)
                Moving image
                argument: ``%s``, position: -1
        learningrate: (a list of items which are a float)
                Comma separated list of learning rates. Learning rate is a scale
                factor on the gradient of the registration objective function
                (gradient with respect to the parameters of the transformation) used
                to update the parameters of the transformation during optimization.
                Smaller values cause the optimizer to take smaller steps through the
                parameter space. Larger values are typically used early in the
                registration process to take large jumps in parameter space followed
                by smaller values to home in on the optimum value of the
                registration objective function. Default is: 0.01, 0.005, 0.0005,
                0.0002. Must have the same number of elements as iterations.
                argument: ``--learningrate %s``
        iterations: (a list of items which are an integer (int or long))
                Comma separated list of iterations. Must have the same number of
                elements as the learning rate.
                argument: ``--iterations %s``
        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
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
                argument: ``%s``, position: -2
        fixedsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to fixed image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--fixedsmoothingfactor %d``

Outputs::

        resampledmovingfilename: (an existing file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
        outputtransform: (an existing file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).

.. _nipype.interfaces.slicer.legacy.registration.MultiResolutionAffineRegistration:


.. index:: MultiResolutionAffineRegistration

MultiResolutionAffineRegistration
---------------------------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L261>`__

Wraps the executable command ``MultiResolutionAffineRegistration ``.

title: Robust Multiresolution Affine Registration

category: Legacy.Registration

description: Provides affine registration using multiple resolution levels and decomposed affine transforms.

version: 0.1.0.$Revision: 2104 $(alpha)

documentation-url: http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/MultiResolutionAffineRegistration

contributor: Casey B Goodlett (Utah)

acknowledgements: This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        resampledImage: (a boolean or a file name)
                Registration results
                argument: ``--resampledImage %s``
        numIterations: (an integer (int or long))
                Number of iterations to run at each resolution level.
                argument: ``--numIterations %d``
        fixedImageMask: (an existing file name)
                Label image which defines a mask of interest for the fixed image
                argument: ``--fixedImageMask %s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        saveTransform: (a boolean or a file name)
                Save the output transform from the registration
                argument: ``--saveTransform %s``
        movingImage: (an existing file name)
                The transform goes from the fixed image's space into the moving
                image's space
                argument: ``%s``, position: -1
        stepSize: (a float)
                The maximum step size of the optimizer in voxels
                argument: ``--stepSize %f``
        stepTolerance: (a float)
                The maximum step size of the optimizer in voxels
                argument: ``--stepTolerance %f``
        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
        metricTolerance: (a float)
                argument: ``--metricTolerance %f``
        numLineIterations: (an integer (int or long))
                Number of iterations to run at each resolution level.
                argument: ``--numLineIterations %d``
        fixedImageROI: (a list of items which are any value)
                Label image which defines a ROI of interest for the fixed image
                argument: ``--fixedImageROI %s``
        fixedImage: (an existing file name)
                Image which defines the space into which the moving image is
                registered
                argument: ``%s``, position: -2

Outputs::

        resampledImage: (an existing file name)
                Registration results
        saveTransform: (an existing file name)
                Save the output transform from the registration

.. _nipype.interfaces.slicer.legacy.registration.RigidRegistration:


.. index:: RigidRegistration

RigidRegistration
-----------------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/slicer/legacy/registration.py#L363>`__

Wraps the executable command ``RigidRegistration ``.

title: Rigid Registration

category: Legacy.Registration

description: Registers two images together using a rigid transform and mutual information.

This module was originally distributed as "Linear registration" but has been renamed to eliminate confusion with the "Affine registration" module.

This module is often used to align images of different subjects or images of the same subject from different modalities.

This module can smooth images prior to registration to mitigate noise and improve convergence. Many of the registration parameters require a working knowledge of the algorithm although the default parameters are sufficient for many registration tasks.



version: 0.1.0.$Revision: 19608 $(alpha)

documentation-url: http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/RigidRegistration

contributor: Daniel Blezek (GE)

acknowledgements: This module was developed by Daniel Blezek while at GE Research with contributions from Jim Miller.

This work is part of the National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149.

Inputs::

        [Optional]
        initialtransform: (an existing file name)
                Initial transform for aligning the fixed and moving image. Maps
                positions in the fixed coordinate frame to positions in the moving
                coordinate frame. Optional.
                argument: ``--initialtransform %s``
        testingmode: (a boolean)
                Enable testing mode. Input transform will be used to construct
                floating image. The floating image will be ignored if passed.
                argument: ``--testingmode ``
        histogrambins: (an integer (int or long))
                Number of histogram bins to use for Mattes Mutual Information.
                Reduce the number of bins if a registration fails. If the number of
                bins is too large, the estimated PDFs will be a field of impulses
                and will inhibit reliable registration estimation.
                argument: ``--histogrambins %d``
        translationscale: (a float)
                Relative scale of translations to rotations, i.e. a value of 100
                means 10mm = 1 degree. (Actual scale used 1/(TranslationScale^2)).
                This parameter is used to 'weight' or 'standardized' the transform
                parameters and their effect on the registration objective function.
                argument: ``--translationscale %f``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        outputtransform: (a boolean or a file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
                argument: ``--outputtransform %s``
        spatialsamples: (an integer (int or long))
                Number of spatial samples to use in estimating Mattes Mutual
                Information. Larger values yield more accurate PDFs and improved
                registration quality.
                argument: ``--spatialsamples %d``
        resampledmovingfilename: (a boolean or a file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
                argument: ``--resampledmovingfilename %s``
        movingsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to moving image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--movingsmoothingfactor %d``
        MovingImageFileName: (an existing file name)
                Moving image
                argument: ``%s``, position: -1
        learningrate: (a list of items which are a float)
                Comma separated list of learning rates. Learning rate is a scale
                factor on the gradient of the registration objective function
                (gradient with respect to the parameters of the transformation) used
                to update the parameters of the transformation during optimization.
                Smaller values cause the optimizer to take smaller steps through the
                parameter space. Larger values are typically used early in the
                registration process to take large jumps in parameter space followed
                by smaller values to home in on the optimum value of the
                registration objective function. Default is: 0.01, 0.005, 0.0005,
                0.0002. Must have the same number of elements as iterations.
                argument: ``--learningrate %s``
        iterations: (a list of items which are an integer (int or long))
                Comma separated list of iterations. Must have the same number of
                elements as the learning rate.
                argument: ``--iterations %s``
        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
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
                argument: ``%s``, position: -2
        fixedsmoothingfactor: (an integer (int or long))
                Amount of smoothing applied to fixed image prior to registration.
                Default is 0 (none). Range is 0-5 (unitless). Consider smoothing the
                input data if there is considerable amounts of noise or the noise
                pattern in the fixed and moving images is very different.
                argument: ``--fixedsmoothingfactor %d``

Outputs::

        resampledmovingfilename: (an existing file name)
                Resampled moving image to the fixed image coordinate frame. Optional
                (specify an output transform or an output volume or both).
        outputtransform: (an existing file name)
                Transform calculated that aligns the fixed and moving image. Maps
                positions in the fixed coordinate frame to the moving coordinate
                frame. Optional (specify an output transform or an output volume or
                both).
