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# interfaces.ants.resampling

## ApplyTransforms

Link to code

Wraps command antsApplyTransforms

ApplyTransforms, applied to an input image, transforms it according to a reference image and a transform (or a set of transforms).

### Examples

    >>> from nipype.interfaces.ants import ApplyTransforms
    >>> at = ApplyTransforms()
    >>> at.inputs.dimension = 3
    >>> at.inputs.input_image = 'moving1.nii'
    >>> at.inputs.reference_image = 'fixed1.nii'
    >>> at.inputs.output_image = 'deformed_moving1.nii'
    >>> at.inputs.interpolation = 'Linear'
    >>> at.inputs.default_value = 0
    >>> at.inputs.transforms = ['trans.mat', 'ants_Warp.nii.gz']
    >>> at.inputs.invert_transform_flags = [False, False]
    >>> at.cmdline
    'antsApplyTransforms --default-value 0 --dimensionality 3 --input moving1.nii --interpolation Linear --output deformed_moving1.nii --reference-image fixed1.nii --transform [trans.mat,0] --transform [ants_Warp.nii.gz,0]'

Inputs:

    [Mandatory]
    input_image: (an existing file name)
            image to apply transformation to (generally a coregistered
            functional)
            flag: --input %s
    reference_image: (an existing file name)
            reference image space that you wish to warp INTO
            flag: --reference-image %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    transforms: (an existing file name)
            flag: %s

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    default_value: (a float, nipype default value: 0.0)
            flag: --default-value %d
    dimension: (2 or 3 or 4)
            This option forces the image to be treated as a specified-
            dimensional image. If not specified, antsWarp tries to infer the
            dimensionality from the input image.
            flag: --dimensionality %d
    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
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    input_image_type: (0 or 1 or 2 or 3)
            Option specifying the input image type of scalar (default), vector,
            tensor, or time series.
            flag: --input-image-type %d
    interpolation: ('Linear' or 'NearestNeighbor' or 'CosineWindowedSinc'
             or 'WelchWindowedSinc' or 'HammingWindowedSinc' or
             'LanczosWindowedSinc' or 'MultiLabel' or 'Gaussian' or 'BSpline',
             nipype default value: Linear)
            flag: %s
    invert_transform_flags: (a boolean)
    num_threads: (an integer, nipype default value: 1)
            Number of ITK threads to use
    out_postfix: (a string, nipype default value: _trans)
            Postfix that is appended to all output files (default = _trans)
    output_image: (a string)
            output file name
            flag: --output %s
    print_out_composite_warp_file: (0 or 1)
            requires: output_image

Outputs:

    output_image: (an existing file name)
            Warped image

## ApplyTransformsToPoints

Link to code

Wraps command antsApplyTransformsToPoints

ApplyTransformsToPoints, applied to an CSV file, transforms coordinates using provided transform (or a set of transforms).

### Examples

    >>> from nipype.interfaces.ants import ApplyTransforms
    >>> at = ApplyTransformsToPoints()
    >>> at.inputs.dimension = 3
    >>> at.inputs.input_file = 'moving.csv'
    >>> at.inputs.transforms = ['trans.mat', 'ants_Warp.nii.gz']
    >>> at.inputs.invert_transform_flags = [False, False]
    >>> at.cmdline
    'antsApplyTransformsToPoints --dimensionality 3 --input moving.csv --output moving_transformed.csv --transform [trans.mat,0] --transform [ants_Warp.nii.gz,0]'

Inputs:

    [Mandatory]
    input_file: (an existing file name)
            Currently, the only input supported is a csv file with columns
            including x,y (2D), x,y,z (3D) or x,y,z,t,label (4D) column
            headers.The points should be defined in physical space.If in doubt
            how to convert coordinates from your files to the spacerequired by
            antsApplyTransformsToPoints try creating/drawing a simplelabel
            volume with only one voxel set to 1 and all others set to 0.Write
            down the voxel coordinates. Then use ImageMaths LabelStats to
            findout what coordinates for this voxel antsApplyTransformsToPoints
            isexpecting.
            flag: --input %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    transforms: (a list of items which are an existing file name)
            transforms that will be applied to the points
            flag: %s

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    dimension: (2 or 3 or 4)
            This option forces the image to be treated as a specified-
            dimensional image. If not specified, antsWarp tries to infer the
            dimensionality from the input image.
            flag: --dimensionality %d
    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
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    invert_transform_flags: (a list of items which are a boolean)
            list indicating if a transform should be reversed
    num_threads: (an integer, nipype default value: 1)
            Number of ITK threads to use
    output_file: (a string)
            Name of the output CSV file
            flag: --output %s

Outputs:

    output_file: (an existing file name)
            csv file with transformed coordinates

## WarpImageMultiTransform

Link to code

Wraps command WarpImageMultiTransform

Warps an image from one space to another

### Examples

    >>> from nipype.interfaces.ants import WarpImageMultiTransform
    >>> wimt = WarpImageMultiTransform()
    >>> wimt.inputs.input_image = 'structural.nii'
    >>> wimt.inputs.reference_image = 'ants_deformed.nii.gz'
    >>> wimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
    >>> wimt.cmdline
    'WarpImageMultiTransform 3 structural.nii structural_wimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz ants_Affine.txt'

    >>> wimt = WarpImageMultiTransform()
    >>> wimt.inputs.input_image = 'diffusion_weighted.nii'
    >>> wimt.inputs.reference_image = 'functional.nii'
    >>> wimt.inputs.transformation_series = ['func2anat_coreg_Affine.txt','func2anat_InverseWarp.nii.gz','dwi2anat_Warp.nii.gz','dwi2anat_coreg_Affine.txt']
    >>> wimt.inputs.invert_affine = [1]
    >>> wimt.cmdline
    'WarpImageMultiTransform 3 diffusion_weighted.nii diffusion_weighted_wimt.nii -R functional.nii -i func2anat_coreg_Affine.txt func2anat_InverseWarp.nii.gz dwi2anat_Warp.nii.gz dwi2anat_coreg_Affine.txt'

Inputs:

    [Mandatory]
    input_image: (a file name)
            image to apply transformation to (generally a coregistered
            functional)
            flag: %s, position: 2
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    transformation_series: (an existing file name)
            transformation file(s) to be applied
            flag: %s, position: -1

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    dimension: (3 or 2, nipype default value: 3)
            image dimension (2 or 3)
            flag: %d, position: 1
    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
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    invert_affine: (a list of items which are an integer)
            List of Affine transformations to invert.E.g.: [1,4,5] inverts the
            1st, 4th, and 5th Affines found in transformation_series. Note that
            indexing starts with 1 and does not include warp fields. Affine
            transformations are distinguished from warp fields by the word
            "affine" included in their filenames.
    num_threads: (an integer, nipype default value: 1)
            Number of ITK threads to use
    out_postfix: (a file name, nipype default value: _wimt)
            Postfix that is prepended to all output files (default = _wimt)
            mutually_exclusive: output_image
    output_image: (a file name)
            name of the output warped image
            flag: %s, position: 3
            mutually_exclusive: out_postfix
    reference_image: (a file name)
            reference image space that you wish to warp INTO
            flag: -R %s
            mutually_exclusive: tightest_box
    reslice_by_header: (a boolean)
            Uses orientation matrix and origin encoded in reference image file
            header. Not typically used with additional transforms
            flag: --reslice-by-header
    tightest_box: (a boolean)
            computes tightest bounding box (overrided by reference_image if
            given)
            flag: --tightest-bounding-box
            mutually_exclusive: reference_image
    use_bspline: (a boolean)
            Use 3rd order B-Spline interpolation
            flag: --use-BSpline
    use_nearest: (a boolean)
            Use nearest neighbor interpolation
            flag: --use-NN

Outputs:

    output_image: (an existing file name)
            Warped image

## WarpTimeSeriesImageMultiTransform

Link to code

Wraps command WarpTimeSeriesImageMultiTransform

Warps a time-series from one space to another

### Examples

    >>> from nipype.interfaces.ants import WarpTimeSeriesImageMultiTransform
    >>> wtsimt = WarpTimeSeriesImageMultiTransform()
    >>> wtsimt.inputs.input_image = 'resting.nii'
    >>> wtsimt.inputs.reference_image = 'ants_deformed.nii.gz'
    >>> wtsimt.inputs.transformation_series = ['ants_Warp.nii.gz','ants_Affine.txt']
    >>> wtsimt.cmdline
    'WarpTimeSeriesImageMultiTransform 4 resting.nii resting_wtsimt.nii -R ants_deformed.nii.gz ants_Warp.nii.gz ants_Affine.txt'

Inputs:

    [Mandatory]
    input_image: (a file name)
            image to apply transformation to (generally a coregistered
            functional)
            flag: %s
    terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
            Control terminal output: `stream` - displays to terminal
            immediately, `allatonce` - waits till command is finished to display
            output, `file` - writes output to file, `none` - output is ignored
    transformation_series: (an existing file name)
            transformation file(s) to be applied
            flag: %s

    [Optional]
    args: (a string)
            Additional parameters to the command
            flag: %s
    dimension: (4 or 3, nipype default value: 4)
            image dimension (3 or 4)
            flag: %d, position: 1
    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
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    invert_affine: (a list of items which are an integer)
            List of Affine transformations to invert. E.g.: [1,4,5] inverts the
            1st, 4th, and 5th Affines found in transformation_series
    num_threads: (an integer, nipype default value: 1)
            Number of ITK threads to use
    out_postfix: (a string, nipype default value: _wtsimt)
            Postfix that is prepended to all output files (default = _wtsimt)
            flag: %s
    reference_image: (a file name)
            reference image space that you wish to warp INTO
            flag: -R %s
            mutually_exclusive: tightest_box
    reslice_by_header: (a boolean)
            Uses orientation matrix and origin encoded in reference image file
            header. Not typically used with additional transforms
            flag: --reslice-by-header
    tightest_box: (a boolean)
            computes tightest bounding box (overrided by reference_image if
            given)
            flag: --tightest-bounding-box
            mutually_exclusive: reference_image
    use_bspline: (a boolean)
            Use 3rd order B-Spline interpolation
            flag: --use-Bspline
    use_nearest: (a boolean)
            Use nearest neighbor interpolation
            flag: --use-NN

Outputs:

    output_image: (an existing file name)
            Warped image