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 = ['ants_Warp.nii.gz', 'trans.mat']
>>> 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 [ ants_Warp.nii.gz, 0 ] --transform [ trans.mat, 0 ]'
>>> at1 = ApplyTransforms()
>>> at1.inputs.dimension = 3
>>> at1.inputs.input_image = 'moving1.nii'
>>> at1.inputs.reference_image = 'fixed1.nii'
>>> at1.inputs.output_image = 'deformed_moving1.nii'
>>> at1.inputs.interpolation = 'BSpline'
>>> at1.inputs.interpolation_parameters = (5,)
>>> at1.inputs.default_value = 0
>>> at1.inputs.transforms = ['ants_Warp.nii.gz', 'trans.mat']
>>> at1.inputs.invert_transform_flags = [False, False]
>>> at1.cmdline 
'antsApplyTransforms --default-value 0 --dimensionality 3 --input moving1.nii --interpolation BSpline[ 5 ] --output deformed_moving1.nii --reference-image fixed1.nii --transform [ ants_Warp.nii.gz, 0 ] --transform [ trans.mat, 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
transforms: (a list of items which are an existing file name)
        transform files: will be applied in reverse order. For example, the
        last specified transform will be applied first.
        flag: %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
default_value: (a float, nipype default value: 0.0)
        flag: --default-value %g
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 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
float: (a boolean)
        Use float instead of double for computations.
        flag: --float %d
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: (u'Linear' or u'NearestNeighbor' or
         u'CosineWindowedSinc' or u'WelchWindowedSinc' or
         u'HammingWindowedSinc' or u'LanczosWindowedSinc' or u'MultiLabel'
         or u'Gaussian' or u'BSpline', nipype default value: Linear)
        flag: %s
interpolation_parameters: (a tuple of the form: (an integer (int or
         long)) or a tuple of the form: (a float, a float))
invert_transform_flags: (a list of items which are a boolean)
num_threads: (an integer (int or long), nipype default value: 1)
        Number of ITK threads to use
out_postfix: (a unicode string, nipype default value: _trans)
        Postfix that is appended to all output files (default = _trans)
output_image: (a unicode string)
        output file name
        flag: --output %s
print_out_composite_warp_file: (a boolean)
        output a composite warp file instead of a transformed image
        requires: output_image
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

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
transforms: (a list of items which are an existing file name)
        transforms that will be applied to the points
        flag: %s

[Optional]
args: (a unicode 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 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
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 (int or long), nipype default value: 1)
        Number of ITK threads to use
output_file: (a unicode string)
        Name of the output CSV file
        flag: --output %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

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
transformation_series: (a list of items which are an existing file
         name)
        transformation file(s) to be applied
        flag: %s, position: -1

[Optional]
args: (a unicode 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 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
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 (int or long))
        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 (int or long), 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
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
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
transformation_series: (a list of items which are an existing file
         name)
        transformation file(s) to be applied
        flag: %s

[Optional]
args: (a unicode 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 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
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 (int or long))
        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 (int or long), nipype default value: 1)
        Number of ITK threads to use
out_postfix: (a unicode 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
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
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