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

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


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


.. index:: AffineRegistration

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

`Link to code <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L73>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

        [Optional]
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
        MovingImageFileName: (an existing file name)
                Moving image
        args: (a string)
                Additional parameters to the command
        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
        fixedsmoothingfactor: (an integer)
                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.
        histogrambins: (an integer)
                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.
        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)
                Initial transform for aligning the fixed and moving image.  Maps positions in the fixed
                coordinate frame to positions in the moving coordinate frame. Optional.
        iterations: (an integer)
                Number of iterations
        movingsmoothingfactor: (an integer)
                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.
        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).
        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).
        spatialsamples: (an integer)
                Number of spatial samples to use in estimating Mattes Mutual Information. Larger values
                yield more accurate PDFs and improved registration quality.
        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.

Outputs::

        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).
        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).

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


.. index:: BSplineDeformableRegistration

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

`Link to code <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L31>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

        [Optional]
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
        MovingImageFileName: (an existing file name)
                Moving image
        args: (a string)
                Additional parameters to the command
        constrain: (a boolean)
                Constrain the deformation to the amount specified in Maximum Deformation
        default: (an integer)
                Default pixel value used if resampling a pixel outside of the volume.
        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
        gridSize: (an integer)
                Number of grid points on interior of the fixed image. Larger grid sizes allow for finer
                registrations.
        histogrambins: (an integer)
                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.
        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)
                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.
        iterations: (an integer)
                Number of iterations
        maximumDeformation: (a float)
                If Constrain Deformation is checked, limit the deformation to this amount.
        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).
        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.
        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).
        spatialsamples: (an integer)
                Number of spatial samples to use in estimating Mattes Mutual Information. Larger values
                yield more accurate PDFs and improved registration quality.

Outputs::

        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.
        resampledmovingfilename: (an existing file name)
                Resampled moving image to fixed image coordinate frame. Optional (specify an output
                transform or an output volume or both).

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


.. index:: ExpertAutomatedRegistration

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

`Link to code <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L277>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

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

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 <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L218>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

        [Optional]
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
        MovingImageFileName: (an existing file name)
                Moving image
        args: (a string)
                Additional parameters to the command
        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
        fixedsmoothingfactor: (an integer)
                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.
        histogrambins: (an integer)
                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.
        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)
                Initial transform for aligning the fixed and moving image. Maps positions in the fixed
                coordinate frame to positions in the moving coordinate frame. Optional.
        iterations: (an integer)
                Comma separated list of iterations. Must have the same number of elements as the
                learning rate.
        learningrate: (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.
        movingsmoothingfactor: (an integer)
                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.
        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).
        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).
        spatialsamples: (an integer)
                Number of spatial samples to use in estimating Mattes Mutual Information. Larger values
                yield more accurate PDFs and improved registration quality.
        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.

Outputs::

        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).
        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).

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


.. index:: MultiResolutionAffineRegistration

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

`Link to code <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L121>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

        [Optional]
        args: (a string)
                Additional parameters to the command
        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
        fixedImage: (an existing file name)
                Image which defines the space into which the moving image is registered
        fixedImageMask: (an existing file name)
                Label image which defines a mask of interest for the fixed image
        fixedImageROI: (a list of items which are any value)
                Label image which defines a ROI of interest for the fixed image
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        metricTolerance: (a float)
        movingImage: (an existing file name)
                The transform goes from the fixed image's space into the moving image's space
        numIterations: (an integer)
                Number of iterations to run at each resolution level.
        numLineIterations: (an integer)
                Number of iterations to run at each resolution level.
        resampledImage: (a boolean or a file name)
                Registration results
        saveTransform: (a boolean or a file name)
                Save the output transform from the registration
        stepSize: (a float)
                The maximum step size of the optimizer in voxels
        stepTolerance: (a float)
                The maximum step size of the optimizer in voxels

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 <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/legacy/registration.py#L165>`__

Wraps 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::

        [Mandatory]
        terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
                Control terminal output

        [Optional]
        FixedImageFileName: (an existing file name)
                Fixed image to which to register
        MovingImageFileName: (an existing file name)
                Moving image
        args: (a string)
                Additional parameters to the command
        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
        fixedsmoothingfactor: (an integer)
                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.
        histogrambins: (an integer)
                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.
        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)
                Initial transform for aligning the fixed and moving image. Maps positions in the fixed
                coordinate frame to positions in the moving coordinate frame. Optional.
        iterations: (an integer)
                Comma separated list of iterations. Must have the same number of elements as the
                learning rate.
        learningrate: (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.
        movingsmoothingfactor: (an integer)
                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.
        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).
        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).
        spatialsamples: (an integer)
                Number of spatial samples to use in estimating Mattes Mutual Information. Larger values
                yield more accurate PDFs and improved registration quality.
        testingmode: (a boolean)
                Enable testing mode. Input transform will be used to construct floating image. The
                floating image will be ignored if passed.
        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.

Outputs::

        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).
        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).
