nipype.interfaces.dipy.reconstruction module

Interfaces to the reconstruction algorithms in dipy

CSD

Link to code

Bases: DipyDiffusionInterface

Uses CSD [Tournier2007] to generate the fODF of DWIs. The interface uses dipy, as explained in dipy’s CSD example.

Tournier2007

Tournier, J.D., et al. NeuroImage 2007. Robust determination of the fibre orientation distribution in diffusion MRI: Non-negativity constrained super-resolved spherical deconvolution

Example

>>> from nipype.interfaces import dipy as ndp
>>> csd = ndp.CSD()
>>> csd.inputs.in_file = '4d_dwi.nii'
>>> csd.inputs.in_bval = 'bvals'
>>> csd.inputs.in_bvec = 'bvecs'
>>> res = csd.run() 
in_bvala pathlike object or string representing an existing file

Input b-values table.

in_bveca pathlike object or string representing an existing file

Input b-vectors table.

in_filea pathlike object or string representing an existing file

Input diffusion data.

b0_thresan integer (int or long)

B0 threshold. (Nipype default value: 700)

in_maska pathlike object or string representing an existing file

Input mask in which compute tensors.

out_fodsa pathlike object or string representing a file

FODFs output file name.

out_prefixa unicode string

Output prefix for file names.

responsea pathlike object or string representing an existing file

Single fiber estimated response.

save_fodsa boolean

Save fODFs in file. (Nipype default value: True)

sh_orderan integer (int or long)

Maximal shperical harmonics order. (Nipype default value: 8)

modela pathlike object or string representing a file

Python pickled object of the CSD model fitted.

out_fodsa pathlike object or string representing a file

FODFs output file name.

EstimateResponseSH

Link to code

Bases: DipyDiffusionInterface

Uses dipy to compute the single fiber response to be used in spherical deconvolution methods, in a similar way to MRTrix’s command estimate_response.

Example

>>> from nipype.interfaces import dipy as ndp
>>> dti = ndp.EstimateResponseSH()
>>> dti.inputs.in_file = '4d_dwi.nii'
>>> dti.inputs.in_bval = 'bvals'
>>> dti.inputs.in_bvec = 'bvecs'
>>> dti.inputs.in_evals = 'dwi_evals.nii'
>>> res = dti.run() 
in_bvala pathlike object or string representing an existing file

Input b-values table.

in_bveca pathlike object or string representing an existing file

Input b-vectors table.

in_evalsa pathlike object or string representing an existing file

Input eigenvalues file.

in_filea pathlike object or string representing an existing file

Input diffusion data.

autoa boolean

Use the auto_response estimator from dipy. Mutually exclusive with inputs: recursive.

b0_thresan integer (int or long)

B0 threshold. (Nipype default value: 700)

fa_thresha float

FA threshold. (Nipype default value: 0.7)

in_maska pathlike object or string representing an existing file

Input mask in which we find single fibers.

out_maska pathlike object or string representing a file

Computed wm mask. (Nipype default value: wm_mask.nii.gz)

out_prefixa unicode string

Output prefix for file names.

recursivea boolean

Use the recursive response estimator from dipy. Mutually exclusive with inputs: auto.

responsea pathlike object or string representing a file

The output response file. (Nipype default value: response.txt)

roi_radiusan integer (int or long)

ROI radius to be used in auto_response. (Nipype default value: 10)

out_maska pathlike object or string representing an existing file

Output wm mask.

responsea pathlike object or string representing an existing file

The response file.

RESTORE

Link to code

Bases: DipyDiffusionInterface

Uses RESTORE [Chang2005] to perform DTI fitting with outlier detection. The interface uses dipy, as explained in dipy’s documentation.

Chang2005

Chang, LC, Jones, DK and Pierpaoli, C. RESTORE: robust estimation of tensors by outlier rejection. MRM, 53:1088-95, (2005).

Example

>>> from nipype.interfaces import dipy as ndp
>>> dti = ndp.RESTORE()
>>> dti.inputs.in_file = '4d_dwi.nii'
>>> dti.inputs.in_bval = 'bvals'
>>> dti.inputs.in_bvec = 'bvecs'
>>> res = dti.run() 
in_bvala pathlike object or string representing an existing file

Input b-values table.

in_bveca pathlike object or string representing an existing file

Input b-vectors table.

in_filea pathlike object or string representing an existing file

Input diffusion data.

b0_thresan integer (int or long)

B0 threshold. (Nipype default value: 700)

in_maska pathlike object or string representing an existing file

Input mask in which compute tensors.

noise_maska pathlike object or string representing an existing file

Input mask in which compute noise variance.

out_prefixa unicode string

Output prefix for file names.

evalsa pathlike object or string representing a file

Output the eigenvalues of the fitted DTI.

evecsa pathlike object or string representing a file

Output the eigenvectors of the fitted DTI.

faa pathlike object or string representing a file

Output fractional anisotropy (FA) map computed from the fitted DTI.

mda pathlike object or string representing a file

Output mean diffusivity (MD) map computed from the fitted DTI.

modea pathlike object or string representing a file

Output mode (MO) map computed from the fitted DTI.

rda pathlike object or string representing a file

Output radial diffusivity (RD) map computed from the fitted DTI.

tracea pathlike object or string representing a file

Output the tensor trace map computed from the fitted DTI.