azhylka

#!/usr/bin/env python3
"""INR-based whole-brain tractography on BIDS wmfod files.

Pipeline per subject / session / FOD variant
--------------------------------------------
1. Train an ImageINR on the wmfod volume  (skipped when checkpoint exists).
2. Export the checkpoint as a TorchScript ``.ts`` file (skipped when it
   already exists alongside the checkpoint).
3. Run :func:`~dipy.tracking.tracker.deterministic_tracking` with
   ``inr_model`` pointing at the ``.ts`` file.

azhylka

#/bin/env bash

do_nonlinear_registration=false

tmp_dir=$(mktemp -d -t tcktransform-XXXXXXXXXX)
cd $tmp_dir

# ____ 0. get DWI data and create two ODFs ____
for sub in sub-02 sub-03; do
wget --quiet https://github.com/MRtrix3/script_test_data/raw/master/BIDS/"${sub}"/dwi/"${sub}"_dwi.bval

azhylka

import nibabel as nib
import vtk
import numpy as np
import vtk.util.numpy_support
import os


def volume2surface(segmentation, out_ply, labels):
    for label in labels:
        print('Label', label)