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()
- Mandatory Inputs
in_bval (a pathlike object or string representing an existing file) – Input b-values table.
in_bvec (a pathlike object or string representing an existing file) – Input b-vectors table.
in_file (a pathlike object or string representing an existing file) – Input diffusion data.
- Optional Inputs
b0_thres (an integer) – B0 threshold. (Nipype default value:
700
)mask_file (a pathlike object or string representing an existing file) – An optional white matter mask.
out_prefix (a string) – Output prefix for file names.
- Outputs
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.
- Mandatory Inputs
in_bval (a pathlike object or string representing an existing file) – Input b-values table.
in_bvec (a pathlike object or string representing an existing file) – Input b-vectors table.
in_file (a pathlike object or string representing an existing file) – Input diffusion data.
- Optional Inputs
b0_thres (an integer) – B0 threshold. (Nipype default value:
700
)mask_file (a pathlike object or string representing an existing file) – An optional white matter mask.
out_prefix (a string) – Output prefix for file names.
- Outputs
out_file (a pathlike object or string representing an existing file)