interfaces.dtitk.registration

AffScalarVol

Link to code

Wraps command affineScalarVolume

Applies affine transform to a scalar volume

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.AffScalarVol()
>>> node.inputs.in_file = 'im1.nii'
>>> node.inputs.transform = 'im_affine.aff'
>>> node.cmdline
'affineScalarVolume -in im1.nii -interp 0 -out im1_affxfmd.nii -trans
 im_affine.aff'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving scalar volume
        flag: -in %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
deformation: (a tuple of the form: (a float, a float, a float, a
         float, a float, a float))
        (xx,yy,zz,xy,yz,xz)
        flag: -deformation %g %g %g %g %g %g
        mutually_exclusive: transform
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
euler: (a tuple of the form: (a float, a float, a float))
        (theta, phi, psi) in degrees
        flag: -euler %g %g %g
        mutually_exclusive: transform
interpolation: ('trilinear' or 'NN', nipype default value: trilinear)
        trilinear or nearest neighbor interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: transform
transform: (an existing file name)
        transform to apply: specify an input transformation file; parameters
        input will be ignored
        flag: -trans %s
        mutually_exclusive: target, translation, euler, deformation
translation: (a tuple of the form: (a float, a float, a float))
        translation (x,y,z) in mm
        flag: -translation %g %g %g
        mutually_exclusive: transform

Outputs:

out_file: (an existing file name)
        moved volume

AffSymTensor3DVol

Link to code

Wraps command affineSymTensor3DVolume

Applies affine transform to a tensor volume

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.AffSymTensor3DVol()
>>> node.inputs.in_file = 'im1.nii'
>>> node.inputs.transform = 'im_affine.aff'
>>> node.cmdline
'affineSymTensor3DVolume -in im1.nii -interp LEI -out im1_affxfmd.nii
 -reorient PPD -trans im_affine.aff'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving tensor volume
        flag: -in %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
deformation: (a tuple of the form: (a float, a float, a float, a
         float, a float, a float))
        (xx,yy,zz,xy,yz,xz)
        flag: -deformation %g %g %g %g %g %g
        mutually_exclusive: transform
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
euler: (a tuple of the form: (a float, a float, a float))
        (theta, phi, psi) in degrees
        flag: -euler %g %g %g
        mutually_exclusive: transform
interpolation: ('LEI' or 'EI', nipype default value: LEI)
        Log Euclidean/Euclidean Interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
reorient: ('PPD' or 'NO' or 'FS', nipype default value: PPD)
        Reorientation strategy: preservation of principal direction, no
        reorientation, or finite strain
        flag: -reorient %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: transform
transform: (an existing file name)
        transform to apply: specify an input transformation file; parameters
        input will be ignored
        flag: -trans %s
        mutually_exclusive: target, translation, euler, deformation
translation: (a tuple of the form: (a float, a float, a float))
        translation (x,y,z) in mm
        flag: -translation %g %g %g
        mutually_exclusive: transform

Outputs:

out_file: (an existing file name)

Affine

Link to code

Wraps command dti_affine_reg

Performs affine registration between two tensor volumes

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.Affine()
>>> node.inputs.fixed_file = 'im1.nii'
>>> node.inputs.moving_file = 'im2.nii'
>>> node.inputs.similarity_metric = 'EDS'
>>> node.inputs.sampling_xyz = (4,4,4)
>>> node.inputs.ftol = 0.01
>>> node.inputs.initialize_xfm = 'im_affine.aff'
>>> node.cmdline
'dti_affine_reg im1.nii im2.nii EDS 4 4 4 0.01 im_affine.aff'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
ftol: (a float, nipype default value: 0.01)
        cost function tolerance
        flag: %g, position: 4
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1
sampling_xyz: (a tuple of the form: (a value of class 'int', a value
         of class 'int', a value of class 'int'), nipype default value: (4,
         4, 4))
        dist between samp points (mm) (x,y,z)
        flag: %g %g %g, position: 3
similarity_metric: ('EDS' or 'GDS' or 'DDS' or 'NMI', nipype default
         value: EDS)
        similarity metric
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
initialize_xfm: (an existing file name)
        Initialize w/DTITK-FORMATaffine
        flag: %s, position: 5

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

AffineTask

Link to code

Wraps command dti_affine_reg

Inputs:

[Mandatory]
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
ftol: (a float, nipype default value: 0.01)
        cost function tolerance
        flag: %g, position: 4
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1
sampling_xyz: (a tuple of the form: (a value of class 'int', a value
         of class 'int', a value of class 'int'), nipype default value: (4,
         4, 4))
        dist between samp points (mm) (x,y,z)
        flag: %g %g %g, position: 3
similarity_metric: ('EDS' or 'GDS' or 'DDS' or 'NMI', nipype default
         value: EDS)
        similarity metric
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
initialize_xfm: (an existing file name)
        Initialize w/DTITK-FORMATaffine
        flag: %s, position: 5

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

ComposeXfm

Link to code

Wraps command dfRightComposeAffine

Combines diffeomorphic and affine transforms

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.ComposeXfm()
>>> node.inputs.in_df = 'im_warp.df.nii'
>>> node.inputs.in_aff= 'im_affine.aff'
>>> node.cmdline
'dfRightComposeAffine -aff im_affine.aff -df im_warp.df.nii -out
 im_warp_affdf.df.nii'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
in_aff: (an existing file name)
        affine transform file
        flag: -aff %s
in_df: (an existing file name)
        diffeomorphic warp file
        flag: -df %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
out_file: (a file name)
        output path
        flag: -out %s

Outputs:

out_file: (an existing file name)

ComposeXfmTask

Link to code

Wraps command dfRightComposeAffine

Inputs:

[Mandatory]
in_aff: (an existing file name)
        affine transform file
        flag: -aff %s
in_df: (an existing file name)
        diffeomorphic warp file
        flag: -df %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
out_file: (a file name)
        output path
        flag: -out %s

Outputs:

out_file: (an existing file name)

Diffeo

Link to code

Wraps command dti_diffeomorphic_reg

Performs diffeomorphic registration between two tensor volumes

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.Diffeo()
>>> node.inputs.fixed_file = 'im1.nii'
>>> node.inputs.moving_file = 'im2.nii'
>>> node.inputs.mask_file = 'mask.nii'
>>> node.inputs.legacy = 1
>>> node.inputs.n_iters = 6
>>> node.inputs.ftol = 0.002
>>> node.cmdline
'dti_diffeomorphic_reg im1.nii im2.nii mask.nii 1 6 0.002'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
ftol: (a float, nipype default value: 0.002)
        iteration for the optimization to stop
        flag: %g, position: 5
legacy: (1, nipype default value: 1)
        legacy parameter; always set to 1
        flag: %d, position: 3
n_iters: (an integer (int or long), nipype default value: 6)
        number of iterations
        flag: %d, position: 4

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
mask_file: (an existing file name)
        mask
        flag: %s, position: 2
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

DiffeoScalarVol

Link to code

Wraps command deformationScalarVolume

Applies diffeomorphic transform to a scalar volume

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.DiffeoScalarVol()
>>> node.inputs.in_file = 'im1.nii'
>>> node.inputs.transform = 'im_warp.df.nii'
>>> node.cmdline
'deformationScalarVolume -in im1.nii -interp 0 -out im1_diffeoxfmd.nii
 -trans im_warp.df.nii'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving scalar volume
        flag: -in %s
transform: (an existing file name)
        transform to apply
        flag: -trans %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
flip: (a tuple of the form: (an integer (int or long), an integer
         (int or long), an integer (int or long)))
        flag: -flip %d %d %d
interpolation: ('trilinear' or 'NN', nipype default value: trilinear)
        trilinear, or nearest neighbor
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
resampling_type: ('backward' or 'forward')
        use backward or forward resampling
        flag: -type %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: voxel_size
voxel_size: (a tuple of the form: (a float, a float, a float))
        xyz voxel size (superseded by target)
        flag: -vsize %g %g %g
        mutually_exclusive: target

Outputs:

out_file: (an existing file name)
        moved volume

DiffeoSymTensor3DVol

Link to code

Wraps command deformationSymTensor3DVolume

Applies diffeomorphic transform to a tensor volume

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.DiffeoSymTensor3DVol()
>>> node.inputs.in_file = 'im1.nii'
>>> node.inputs.transform = 'im_warp.df.nii'
>>> node.cmdline
'deformationSymTensor3DVolume -df FD -in im1.nii -interp LEI -out
 im1_diffeoxfmd.nii -reorient PPD -trans im_warp.df.nii'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving tensor volume
        flag: -in %s
transform: (an existing file name)
        transform to apply
        flag: -trans %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
df: (a unicode string, nipype default value: FD)
        flag: -df %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
flip: (a tuple of the form: (an integer (int or long), an integer
         (int or long), an integer (int or long)))
        flag: -flip %d %d %d
interpolation: ('LEI' or 'EI', nipype default value: LEI)
        Log Euclidean/Euclidean Interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
reorient: ('PPD' or 'FS', nipype default value: PPD)
        Reorientation strategy: preservation of principal direction or
        finite strain
        flag: -reorient %s
resampling_type: ('backward' or 'forward')
        use backward or forward resampling
        flag: -type %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: voxel_size
voxel_size: (a tuple of the form: (a float, a float, a float))
        xyz voxel size (superseded by target)
        flag: -vsize %g %g %g
        mutually_exclusive: target

Outputs:

out_file: (an existing file name)

DiffeoTask

Link to code

Wraps command dti_diffeomorphic_reg

Inputs:

[Mandatory]
ftol: (a float, nipype default value: 0.002)
        iteration for the optimization to stop
        flag: %g, position: 5
legacy: (1, nipype default value: 1)
        legacy parameter; always set to 1
        flag: %d, position: 3
n_iters: (an integer (int or long), nipype default value: 6)
        number of iterations
        flag: %d, position: 4

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
mask_file: (an existing file name)
        mask
        flag: %s, position: 2
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

Rigid

Link to code

Wraps command dti_rigid_reg

Performs rigid registration between two tensor volumes

Example

>>> from nipype.interfaces import dtitk
>>> node = dtitk.Rigid()
>>> node.inputs.fixed_file = 'im1.nii'
>>> node.inputs.moving_file = 'im2.nii'
>>> node.inputs.similarity_metric = 'EDS'
>>> node.inputs.sampling_xyz = (4,4,4)
>>> node.inputs.ftol = 0.01
>>> node.cmdline
'dti_rigid_reg im1.nii im2.nii EDS 4 4 4 0.01'
>>> node.run() # doctest: +SKIP

Inputs:

[Mandatory]
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
ftol: (a float, nipype default value: 0.01)
        cost function tolerance
        flag: %g, position: 4
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1
sampling_xyz: (a tuple of the form: (a value of class 'int', a value
         of class 'int', a value of class 'int'), nipype default value: (4,
         4, 4))
        dist between samp points (mm) (x,y,z)
        flag: %g %g %g, position: 3
similarity_metric: ('EDS' or 'GDS' or 'DDS' or 'NMI', nipype default
         value: EDS)
        similarity metric
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
initialize_xfm: (an existing file name)
        Initialize w/DTITK-FORMATaffine
        flag: %s, position: 5

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

RigidTask

Link to code

Wraps command dti_rigid_reg

Inputs:

[Mandatory]
fixed_file: (an existing file name)
        fixed tensor volume
        flag: %s, position: 0
ftol: (a float, nipype default value: 0.01)
        cost function tolerance
        flag: %g, position: 4
moving_file: (an existing file name)
        moving tensor volume
        flag: %s, position: 1
sampling_xyz: (a tuple of the form: (a value of class 'int', a value
         of class 'int', a value of class 'int'), nipype default value: (4,
         4, 4))
        dist between samp points (mm) (x,y,z)
        flag: %g %g %g, position: 3
similarity_metric: ('EDS' or 'GDS' or 'DDS' or 'NMI', nipype default
         value: EDS)
        similarity metric
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
initialize_xfm: (an existing file name)
        Initialize w/DTITK-FORMATaffine
        flag: %s, position: 5

Outputs:

out_file: (an existing file name)
out_file_xfm: (an existing file name)

affScalarVolTask

Link to code

Wraps command affineScalarVolume

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving scalar volume
        flag: -in %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
deformation: (a tuple of the form: (a float, a float, a float, a
         float, a float, a float))
        (xx,yy,zz,xy,yz,xz)
        flag: -deformation %g %g %g %g %g %g
        mutually_exclusive: transform
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
euler: (a tuple of the form: (a float, a float, a float))
        (theta, phi, psi) in degrees
        flag: -euler %g %g %g
        mutually_exclusive: transform
interpolation: ('trilinear' or 'NN', nipype default value: trilinear)
        trilinear or nearest neighbor interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: transform
transform: (an existing file name)
        transform to apply: specify an input transformation file; parameters
        input will be ignored
        flag: -trans %s
        mutually_exclusive: target, translation, euler, deformation
translation: (a tuple of the form: (a float, a float, a float))
        translation (x,y,z) in mm
        flag: -translation %g %g %g
        mutually_exclusive: transform

Outputs:

out_file: (an existing file name)
        moved volume

affSymTensor3DVolTask

Link to code

Wraps command affineSymTensor3DVolume

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving tensor volume
        flag: -in %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
deformation: (a tuple of the form: (a float, a float, a float, a
         float, a float, a float))
        (xx,yy,zz,xy,yz,xz)
        flag: -deformation %g %g %g %g %g %g
        mutually_exclusive: transform
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
euler: (a tuple of the form: (a float, a float, a float))
        (theta, phi, psi) in degrees
        flag: -euler %g %g %g
        mutually_exclusive: transform
interpolation: ('LEI' or 'EI', nipype default value: LEI)
        Log Euclidean/Euclidean Interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
reorient: ('PPD' or 'NO' or 'FS', nipype default value: PPD)
        Reorientation strategy: preservation of principal direction, no
        reorientation, or finite strain
        flag: -reorient %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: transform
transform: (an existing file name)
        transform to apply: specify an input transformation file; parameters
        input will be ignored
        flag: -trans %s
        mutually_exclusive: target, translation, euler, deformation
translation: (a tuple of the form: (a float, a float, a float))
        translation (x,y,z) in mm
        flag: -translation %g %g %g
        mutually_exclusive: transform

Outputs:

out_file: (an existing file name)

diffeoScalarVolTask

Link to code

Wraps command deformationScalarVolume

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving scalar volume
        flag: -in %s
transform: (an existing file name)
        transform to apply
        flag: -trans %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
flip: (a tuple of the form: (an integer (int or long), an integer
         (int or long), an integer (int or long)))
        flag: -flip %d %d %d
interpolation: ('trilinear' or 'NN', nipype default value: trilinear)
        trilinear, or nearest neighbor
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
resampling_type: ('backward' or 'forward')
        use backward or forward resampling
        flag: -type %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: voxel_size
voxel_size: (a tuple of the form: (a float, a float, a float))
        xyz voxel size (superseded by target)
        flag: -vsize %g %g %g
        mutually_exclusive: target

Outputs:

out_file: (an existing file name)
        moved volume

diffeoSymTensor3DVolTask

Link to code

Wraps command deformationSymTensor3DVolume

Inputs:

[Mandatory]
in_file: (an existing file name)
        moving tensor volume
        flag: -in %s
transform: (an existing file name)
        transform to apply
        flag: -trans %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
df: (a unicode string, nipype default value: FD)
        flag: -df %s
environ: (a dictionary with keys which are a bytes or None or a value
         of class 'str' and with values which are a bytes or None or a value
         of class 'str', nipype default value: {})
        Environment variables
flip: (a tuple of the form: (an integer (int or long), an integer
         (int or long), an integer (int or long)))
        flag: -flip %d %d %d
interpolation: ('LEI' or 'EI', nipype default value: LEI)
        Log Euclidean/Euclidean Interpolation
        flag: -interp %s
out_file: (a file name)
        output filename
        flag: -out %s
reorient: ('PPD' or 'FS', nipype default value: PPD)
        Reorientation strategy: preservation of principal direction or
        finite strain
        flag: -reorient %s
resampling_type: ('backward' or 'forward')
        use backward or forward resampling
        flag: -type %s
target: (an existing file name)
        output volume specification read from the target volume if specified
        flag: -target %s
        mutually_exclusive: voxel_size
voxel_size: (a tuple of the form: (a float, a float, a float))
        xyz voxel size (superseded by target)
        flag: -vsize %g %g %g
        mutually_exclusive: target

Outputs:

out_file: (an existing file name)