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# workflows.dmri.mrtrix.diffusion

## `create_mrtrix_dti_pipeline()`

Link to code

Creates a pipeline that does the same diffusion processing as in the dmri_mrtrix_dti example script. Given a diffusion-weighted image, b-values, and b-vectors, the workflow will return the tractography computed from spherical deconvolution and probabilistic streamline tractography

### Example

    >>> dti = create_mrtrix_dti_pipeline("mrtrix_dti")
    >>> dti.inputs.inputnode.dwi = 'data.nii'
    >>> dti.inputs.inputnode.bvals = 'bvals'
    >>> dti.inputs.inputnode.bvecs = 'bvecs'
    >>> dti.run()

Inputs:

    inputnode.dwi
    inputnode.bvecs
    inputnode.bvals

Outputs:

    outputnode.fa
    outputnode.tdi
    outputnode.tracts_tck
    outputnode.tracts_trk
    outputnode.csdeconv

### Graph