nipype.interfaces.dipy.tensors module¶
DTI¶
Bases: DipyDiffusionInterface
Calculates the diffusion tensor model parameters
Example
>>> import nipype.interfaces.dipy as dipy >>> dti = dipy.DTI() >>> dti.inputs.in_file = 'diffusion.nii' >>> dti.inputs.in_bvec = 'bvecs' >>> dti.inputs.in_bval = 'bvals' >>> 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
)- mask_filea pathlike object or string representing an existing file
An optional white matter mask.
- out_prefixa unicode string
Output prefix for file names.
ad_file : a pathlike object or string representing an existing file color_fa_file : a pathlike object or string representing an existing file fa_file : a pathlike object or string representing an existing file md_file : a pathlike object or string representing an existing file out_file : a pathlike object or string representing an existing file rd_file : a pathlike object or string representing an existing file
TensorMode¶
Bases: DipyDiffusionInterface
Creates a map of the mode of the diffusion tensors given a set of diffusion-weighted images, as well as their associated b-values and b-vectors 1. Fits the diffusion tensors and calculates tensor mode with Dipy.
Example
>>> import nipype.interfaces.dipy as dipy >>> mode = dipy.TensorMode() >>> mode.inputs.in_file = 'diffusion.nii' >>> mode.inputs.in_bvec = 'bvecs' >>> mode.inputs.in_bval = 'bvals' >>> mode.run()References
- 1
Daniel B. Ennis and G. Kindlmann, “Orthogonal Tensor Invariants and the Analysis of Diffusion Tensor Magnetic Resonance Images”, Magnetic Resonance in Medicine, vol. 55, no. 1, pp. 136-146, 2006.
- 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
)- mask_filea pathlike object or string representing an existing file
An optional white matter mask.
- out_prefixa unicode string
Output prefix for file names.
out_file : a pathlike object or string representing an existing file