b0 = hardi_data[..., gtab.b0s_mask]
mean_b0 = np.mean(b0, -1)
ni_b0 = nib.Nifti1Image(mean_b0, hardi_affine)
ni_b0.to_filename('mean_b0.nii')
plt.matshow(mean_b0[:, :, mean_b0.shape[-1] // 2], cmap=cm.bone)
MNI_T2 = dpd.read_mni_template()
MNI_T2_data = MNI_T2.get_data()
MNI_T2_affine = MNI_T2.get_affine()
level_iters = [10, 10, 5]
dim = 3
metric = CCMetric(dim)
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters, step_length=0.25)
sdr.verbosity = VerbosityLevels.DIAGNOSE
mapping = sdr.optimize(MNI_T2_data, mean_b0, MNI_T2_affine, hardi_affine)
warped_b0 = mapping.transform(mean_b0)
plt.matshow(warped_b0[:, :, warped_b0.shape[-1] // 2], cmap=cm.bone)
plt.matshow(MNI_T2_data[:, :, MNI_T2_data.shape[-1] // 2], cmap=cm.bone)
new_ni = nib.Nifti1Image(warped_b0, MNI_T2_affine)
new_ni.to_filename('./warped_b0.nii.gz')
afqpath = 'D:/opt/AFQ/'
LOCC_ni = nib.load(
os.path.join(afqpath, 'templates/callosum2/L_Occipital.nii.gz'))
ROCC_ni = nib.load(
os.path.join(afqpath, 'templates/callosum2/R_Occipital.nii.gz'))
midsag_ni = nib.load(
os.path.join(afqpath, 'templates/callosum2/Callosum_midsag.nii.gz'))
import nibabel as nib from dipy.align.imwarp import SymmetricDiffeomorphicRegistration from dipy.align.metrics import CCMetric f_t1 = '/home/eleftherios/Data/reg/t1_fa.nii.gz' f_fa = '/home/eleftherios/Data/reg/fa.nii.gz' t1 = nib.load(f_t1).get_data() img = nib.load(f_fa) fa = img.get_data() fa_aff = img.get_affine() cc = CCMetric(3) sdr = SymmetricDiffeomorphicRegistration(metric=cc) sdr.verbosity = 2 sdm = sdr.optimize(static=fa, moving=t1) t1_warped = sdm.transform(t1) f_t1_warped = '/home/eleftherios/Data/reg/t1_fa_warped.nii.gz' nib.save(nib.Nifti1Image(t1_warped, fa_aff), f_t1_warped)
with open(config_fname,'r') as f:
options = [tuple(line.strip().split()) for line in f.readlines()]
options = {opt[0]:opt[1] for opt in options}
else:
options = {}
step_length = float(options.get('step_length', '0.25'))
inv_tol = float(options.get('inv_tol', '1e-3'))
inv_iter = int(options.get('inv_iter', '20'))
experiment_name = options.get('experiment_name')
level_iters = [400, 200, 100, 50, 25]
dim = 3
metric = SSDMetric(dim, smooth=3)
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters, inv_iter=inv_iter, inv_tol=inv_tol, opt_tol=1e-6, step_length=step_length, ss_sigma_factor=1.0)
sdr.verbosity = VerbosityLevels.DIAGNOSE
start = time.time()
mapping = sdr.optimize(cup, sphere)
end = time.time()
elapsed = end - start
print('Elapsed: %e'%(elapsed,))
fwd = np.array(mapping.forward)
bwd = np.array(mapping.backward)
# Get deformed mid slices
z0 = fwd.shape[2]//2
whlines, wvlines = get_deformed_grid(fwd, [z0])
fwd_fname = 'fwd_lines_%s.p'%(experiment_name,)
pickle.dump((whlines, wvlines), open(fwd_fname,'wb'))
ibsr_bw_affmap = dipy_align(ibsr1, ibsr1_affine, brainweb, brainweb_affine)
pickle.dump(ibsr_bw_affmap, open(aff_name, "w"))
bw_on_ibsr1 = ibsr_bw_affmap.transform(brainweb)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=0) # aligned (sagital view)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=1) # aligned (axial view)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=2) # aligned (coronal view)
# Start diffeomorphic registration
diff_name = "ibsr1_to_brainweb_diff.p"
if os.path.isfile(diff_name):
ibsr_bw_diffmap = pickle.load(open(diff_name, "r"))
else:
metric = CCMetric(3)
level_iters = [50, 10]
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters)
sdr.verbosity = VerbosityLevels.DEBUG
ibsr_bw_diffmap = sdr.optimize(ibsr1, brainweb, ibsr1_affine, brainweb_affine, ibsr_bw_affmap.affine)
pickle.dump(ibsr_bw_diffmap, open(diff_name, "w"))
bw_warped_ibsr1 = ibsr_bw_diffmap.transform(brainweb)
rt.overlay_slices(ibsr1, bw_warped_ibsr1, slice_type=0) # warped (sagital view)
rt.overlay_slices(ibsr1, bw_warped_ibsr1, slice_type=1) # warped (axial view)
rt.overlay_slices(ibsr1, bw_warped_ibsr1, slice_type=2) # warped (coronal view)
# Now the initial segmentation
bw_mask_ibsr1 = ibsr_bw_diffmap.transform(brainweb_mask)
bw_mask_ibsr1 = bw_mask_ibsr1 > 0
# Dilate
structure = np.ones((5, 5, 5))
dilated_mask = binary_dilation(bw_mask_ibsr1, structure)
ibsr_bw_affmap = dipy_align(ibsr1, ibsr1_affine, brainweb, brainweb_affine)
pickle.dump(ibsr_bw_affmap, open(aff_name, 'w'))
bw_on_ibsr1 = ibsr_bw_affmap.transform(brainweb)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=0) # aligned (sagital view)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=1) # aligned (axial view)
rt.overlay_slices(ibsr1, bw_on_ibsr1, slice_type=2) # aligned (coronal view)
# Start diffeomorphic registration
diff_name = 'ibsr1_to_brainweb_diff.p'
if os.path.isfile(diff_name):
ibsr_bw_diffmap = pickle.load(open(diff_name, 'r'))
else:
metric = CCMetric(3)
level_iters = [50, 10]
sdr = SymmetricDiffeomorphicRegistration(metric, level_iters)
sdr.verbosity = VerbosityLevels.DEBUG
ibsr_bw_diffmap = sdr.optimize(ibsr1, brainweb, ibsr1_affine,
brainweb_affine, ibsr_bw_affmap.affine)
pickle.dump(ibsr_bw_diffmap, open(diff_name, 'w'))
bw_warped_ibsr1 = ibsr_bw_diffmap.transform(brainweb)
rt.overlay_slices(ibsr1, bw_warped_ibsr1,
slice_type=0) # warped (sagital view)
rt.overlay_slices(ibsr1, bw_warped_ibsr1, slice_type=1) # warped (axial view)
rt.overlay_slices(ibsr1, bw_warped_ibsr1,
slice_type=2) # warped (coronal view)
# Now the initial segmentation
bw_mask_ibsr1 = ibsr_bw_diffmap.transform(brainweb_mask)
bw_mask_ibsr1 = bw_mask_ibsr1 > 0
