nipype.interfaces.dipy.tensors module

DTI

Link to code

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

Link to code

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)