interfaces.dipy.tensors¶
DTI¶
Calculates the diffusion tensor model parameters
Example¶
>>> import nipype.interfaces.dipy as dipy
>>> dti = dipy.DTI()
>>> dti.inputs.in_file = 'diffusion.nii'
>>> dti.inputs.bvecs = 'bvecs'
>>> dti.inputs.bvals = 'bvals'
>>> dti.run()
Inputs:
[Mandatory]
bvals: (an existing file name)
The input b-value text file
bvecs: (an existing file name)
The input b-vector text file
in_file: (an existing file name)
The input 4D diffusion-weighted image file
[Optional]
mask_file: (an existing file name)
An optional white matter mask
out_filename: (a file name)
The output filename for the DTI parameters image
Outputs:
out_file: (an existing file name)
TensorMode¶
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. Fits the diffusion tensors and calculates tensor mode with Dipy.
[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. |
Example¶
>>> import nipype.interfaces.dipy as dipy
>>> mode = dipy.TensorMode()
>>> mode.inputs.in_file = 'diffusion.nii'
>>> mode.inputs.bvecs = 'bvecs'
>>> mode.inputs.bvals = 'bvals'
>>> mode.run()
Inputs:
[Mandatory]
bvals: (an existing file name)
The input b-value text file
bvecs: (an existing file name)
The input b-vector text file
in_file: (an existing file name)
The input 4D diffusion-weighted image file
[Optional]
mask_file: (an existing file name)
An optional white matter mask
out_filename: (a file name)
The output filename for the Tensor mode image
Outputs:
out_file: (an existing file name)
tensor_fitting()
¶
Use dipy to fit DTI
Parameters¶
- in_file : str
- Full path to a DWI data file.
- bvals : str
- Full path to a file containing gradient magnitude information (b-values).
- bvecs : str
- Full path to a file containing gradient direction information (b-vectors).
- mask_file : str, optional
- Full path to a file containing a binary mask. Defaults to use the entire volume.
Returns¶
TensorFit object, affine