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

interfaces.slicer.filtering.resamplescalarvectordwivolume
=========================================================


.. _nipype.interfaces.slicer.filtering.resamplescalarvectordwivolume.ResampleScalarVectorDWIVolume:


.. index:: ResampleScalarVectorDWIVolume

ResampleScalarVectorDWIVolume
-----------------------------

`Link to code <http://github.com/nipy/nipype/tree/9595f272aa4086ea28f7534a8bd05690f60bf6b8/nipype/interfaces/slicer/filtering/resamplescalarvectordwivolume.py#L40>`__

Wraps command **ResampleScalarVectorDWIVolume **

title: Resample Scalar/Vector/DWI Volume

category: Filtering

description: This module implements image and vector-image resampling through  the use of itk Transforms.It can also handle diffusion weighted MRI image resampling. "Resampling" is performed in space coordinates, not pixel/grid coordinates. It is quite important to ensure that image spacing is properly set on the images involved. The interpolator is required since the mapping from one space to the other will often require evaluation of the intensity of the image at non-grid positions.

Warning: To resample DWMR Images, use nrrd input and output files.

Warning: Do not use to resample Diffusion Tensor Images, tensors would  not be reoriented

version: 0.1

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

contributor: Francois Budin (UNC)

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. Information on the National Centers for Biomedical Computing can be obtained from http://nihroadmap.nih.gov/bioinformatics

Inputs::

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

        [Optional]
        Inverse_ITK_Transformation: (a boolean)
                Inverse the transformation before applying it from output image to input image
        Reference: (an existing file name)
                Reference Volume (spacing,size,orientation,origin)
        args: (a string)
                Additional parameters to the command
        centered_transform: (a boolean)
                Set the center of the transformation to the center of the input image
        defField: (an existing file name)
                File containing the deformation field (3D vector image containing vectors with 3
                components)
        default_pixel_value: (a float)
                Default pixel value for samples falling outside of the input region
        direction_matrix: (a float)
                9 parameters of the direction matrix by rows (ijk to LPS if LPS transform, ijk to RAS if
                RAS transform)
        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
        hfieldtype: ('displacement' or 'h-Field')
                Set if the deformation field is an h-Field
        ignore_exception: (a boolean, nipype default value: False)
                Print an error message instead of throwing an exception in case the interface fails to
                run
        image_center: ('input' or 'output')
                Image to use to center the transform (used only if 'Centered Transform' is selected)
        inputVolume: (an existing file name)
                Input Volume to be resampled
        interpolation: ('linear' or 'nn' or 'ws' or 'bs')
                Sampling algorithm (linear or nn (nearest neighborhoor), ws (WindowedSinc), bs (BSpline)
                ~
        notbulk: (a boolean)
                The transform following the BSpline transform is not set as a bulk transform for the
                BSpline transform
        number_of_thread: (an integer)
                Number of thread used to compute the output image
        origin: (a list of items which are any value)
                Origin of the output Image
        outputVolume: (a boolean or a file name)
                Resampled Volume
        rotation_point: (a list of items which are any value)
                Rotation Point in case of rotation around a point (otherwise useless)
        size: (a float)
                Size along each dimension (0 means use input size)
        spaceChange: (a boolean)
                Space Orientation between transform and image is different (RAS/LPS) (warning: if the
                transform is a Transform Node in Slicer3, do not select)
        spacing: (a float)
                Spacing along each dimension (0 means use input spacing)
        spline_order: (an integer)
                Spline Order
        transform: ('rt' or 'a')
                Transform algorithm, rt = Rigid Transform, a = Affine Transform
        transform_matrix: (a float)
                12 parameters of the transform matrix by rows ( --last 3 being translation-- )
        transform_order: ('input-to-output' or 'output-to-input')
                Select in what order the transforms are read
        transformationFile: (an existing file name)
        window_function: ('h' or 'c' or 'w' or 'l' or 'b')
                Window Function , h = Hamming , c = Cosine , w = Welch , l = Lanczos , b = Blackman

Outputs::

        outputVolume: (an existing file name)
                Resampled Volume
