nii2voi.py

from collections import OrderedDict

import nibabel as nib

from brainvoyagertools import voi  # Get it from https://github.com/fladd/brainvoyagertools


v1 = voi.VOIsDefinition(framing_cube=256, reference_space="MNI")
v2 = voi.VOIsDefinition(framing_cube=256, reference_space="MNI")

#img = nib.load("Parcels_MNI_111_256_mni.nii.gz")
img = nib.load("Parcels_MNI_111_mni.nii")
data = img.get_fdata()
d = OrderedDict()

for i in range(img.shape[0]):
    print(i)
    for j in range(img.shape[1]):
        for k in range(img.shape[2]):
            try:
                #d[data[i][j][k]].append([j, k, i])
                d[data[i][j][k]].append(nib.affines.apply_affine(img.affine, [i, j, k]))
            except:
                d[data[i][j][k]] = []
                d[data[i][j][k]].append(nib.affines.apply_affine(img.affine, [i, j, k]))
                #d[data[i][j][k]].append([j, k, i])

for x in sorted(d):
    if x != 0:
        if x < 256:
            v1.add_voi(voi.VOI(int(x), d[x], colour=[0,0,255]))
        else:
            v2.add_voi(voi.VOI(int(x), d[x], colour=[0,0,255]))

v1.save("Parcels_MNI_111_orig_1-255")
v2.save("Parcels_MNI_111_orig_256-333")