else:
from dipy.data import read_stanford_hardi
hardi_img, gtab = read_stanford_hardi()
data = hardi_img.get_data()
vox_size = hardi_img.header.get_zooms()[0]
The second one will be the T2-contrast MNI template image, which we"ll need to
After Change
data, affine, hardi_img = load_nifti(hardi_fname, return_img=True)
vox_size = hardi_img.header.get_zooms()[0]
bvals, bvecs = read_bvals_bvecs(hardi_bval, hardi_bvec)
gtab = gradient_table(bvals, bvecs)
The second one will be the T2-contrast MNI template image, which we"ll need to
reslice to 2x2x2 mm isotropic voxel resolution to match the HARDI data.
