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interfaces.dipy.tensors

DTI

Link to code

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

Link to code

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()

Link to code

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