nipype.interfaces.dipy.tracks module

StreamlineTractography

Link to code

Bases: DipyBaseInterface

Streamline tractography using EuDX [Garyfallidis12].

[Garyfallidis12]

Garyfallidis E., “Towards an accurate brain tractography”, PhD thesis, University of Cambridge, 2012

Example

>>> from nipype.interfaces import dipy as ndp
>>> track = ndp.StreamlineTractography()
>>> track.inputs.in_file = '4d_dwi.nii'
>>> track.inputs.in_model = 'model.pklz'
>>> track.inputs.tracking_mask = 'dilated_wm_mask.nii'
>>> res = track.run() # doctest: +SKIP

gfa_thresh : a float

GFA threshold to compute tracking mask. (Nipype default value: 0.2)

in_file : a pathlike object or string representing an existing file

Input diffusion data.

min_angle : a float

Minimum separation angle. (Nipype default value: 25.0)

multiprocess : a boolean

Use multiprocessing. (Nipype default value: True)

num_seeds : an integer (int or long)

Desired number of tracks in tractography. (Nipype default value: 10000)

peak_threshold : a float

Threshold to consider peaks from model. (Nipype default value: 0.5)

save_seeds : a boolean

Save seeding voxels coordinates. (Nipype default value: False)

in_model : a pathlike object or string representing an existing file

Input f/d-ODF model extracted from.

in_peaks : a pathlike object or string representing an existing file

Peaks computed from the odf.

out_prefix : a unicode string

Output prefix for file names.

seed_coord : a pathlike object or string representing an existing file

File containing the list of seed voxel coordinates (N,3).

seed_mask : a pathlike object or string representing an existing file

Input mask within which perform seeding.

tracking_mask : a pathlike object or string representing an existing file

Input mask within which perform tracking.

gfa : a pathlike object or string representing a file

The resulting GFA (generalized FA) computed using the peaks of the ODF.

odf_peaks : a pathlike object or string representing a file

Peaks computed from the odf.

out_seeds : a pathlike object or string representing a file

File containing the (N,3) voxel coordinates used in seeding.

tracks : a pathlike object or string representing a file

TrackVis file containing extracted streamlines.

TrackDensityMap

Link to code

Bases: DipyBaseInterface

Creates a tract density image from a TrackVis track file using functions from dipy

Example

>>> import nipype.interfaces.dipy as dipy
>>> trk2tdi = dipy.TrackDensityMap()
>>> trk2tdi.inputs.in_file = 'converted.trk'
>>> trk2tdi.run()                                   # doctest: +SKIP

in_file : a pathlike object or string representing an existing file

The input TrackVis track file.

data_dims : a list of from 3 to 3 items which are an integer (int or long)

The size of the image in voxels.

out_filename : a pathlike object or string representing a file

The output filename for the tracks in TrackVis (.trk) format. (Nipype default value: tdi.nii)

points_space : ‘rasmm’ or ‘voxel’ or None

Coordinates of trk file. (Nipype default value: rasmm)

reference : a pathlike object or string representing an existing file

A reference file to define RAS coordinates space.

voxel_dims : a list of from 3 to 3 items which are a float

The size of each voxel in mm.

out_file : a pathlike object or string representing an existing file