nipype.interfaces.mrtrix.convert module

MRTrix2TrackVis

Link to code

Bases: DipyBaseInterface

Converts MRtrix (.tck) tract files into TrackVis (.trk) format using functions from dipy .. rubric:: Example

>>> import nipype.interfaces.mrtrix as mrt
>>> tck2trk = mrt.MRTrix2TrackVis()
>>> tck2trk.inputs.in_file = 'dwi_CSD_tracked.tck'
>>> tck2trk.inputs.image_file = 'diffusion.nii'
>>> tck2trk.run()                                   

Mandatory Inputs

in_file (a pathlike object or string representing an existing file) – The input file for the tracks in MRTrix (.tck) format.

Optional Inputs

• image_file (a pathlike object or string representing an existing file) – The image the tracks were generated from.

• matrix_file (a pathlike object or string representing an existing file) – A transformation matrix to apply to the tracts after they have been generated (from FLIRT - affine transformation from image_file to registration_image_file).

• out_filename (a pathlike object or string representing a file) – The output filename for the tracks in TrackVis (.trk) format. (Nipype default value: converted.trk)

• registration_image_file (a pathlike object or string representing an existing file) – The final image the tracks should be registered to.

Outputs

out_file (a pathlike object or string representing an existing file)

nipype.interfaces.mrtrix.convert.get_data_dims(volume)

nipype.interfaces.mrtrix.convert.get_vox_dims(volume)

nipype.interfaces.mrtrix.convert.read_mrtrix_header(in_file)

nipype.interfaces.mrtrix.convert.read_mrtrix_streamlines(in_file, header, as_generator=True)

nipype.interfaces.mrtrix.convert.read_mrtrix_tracks(in_file, as_generator=True)

nipype.interfaces.mrtrix.convert.transform_to_affine(streams, header, affine)