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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.in_bvec = 'bvecs'
    >>> dti.inputs.in_bval = 'bvals'
    >>> dti.run()

Inputs:

    [Mandatory]
    in_bval: (an existing file name)
            input b-values table
    in_bvec: (an existing file name)
            input b-vectors table
    in_file: (an existing file name)
            input diffusion data

    [Optional]
    b0_thres: (an integer (int or long), nipype default value: 700)
            b0 threshold
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    mask_file: (an existing file name)
            An optional white matter mask
    out_prefix: (a unicode string)
            output prefix for file names

Outputs:

    ad_file: (an existing file name)
    fa_file: (an existing file name)
    md_file: (an existing file name)
    out_file: (an existing file name)
    rd_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.in_bvec = 'bvecs'
    >>> mode.inputs.in_bval = 'bvals'
    >>> mode.run()

Inputs:

    [Mandatory]
    in_bval: (an existing file name)
            input b-values table
    in_bvec: (an existing file name)
            input b-vectors table
    in_file: (an existing file name)
            input diffusion data

    [Optional]
    b0_thres: (an integer (int or long), nipype default value: 700)
            b0 threshold
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    mask_file: (an existing file name)
            An optional white matter mask
    out_prefix: (a unicode string)
            output prefix for file names

Outputs:

    out_file: (an existing file name)