def dump(self, path):
nb.save(self.img, os.path.join(path, 'subject.nii'))
reg = nr.resample(self.timg, self.T.inv(), reference=self.img)
nb.save(self.timg, os.path.join(path, 'template_reg.nii'))
hip_reg = self.get_mask('left') + self.get_mask('right')
hip_reg = nb.Nifti1Image(hip_reg, self.img.get_affine())
nb.save(hip_reg, os.path.join(path, os.path.join('hip_reg.nii')))
if self.lhip_mask != None and self.rhip_mask != None:
hip = self.lhip_mask + self.rhip_mask
hip = nb.Nifti1Image(hip.astype('uint8'), self.img.get_affine())
nb.save(hip, os.path.join(path, 'hip_gold.nii'))
# Uncache template image to free memory
self.timg.uncache()
def get_mask(self, hemi):
"""
Resample template mask
"""
if hemi == 'left':
if self.tlhip_reg_mask != None:
return self.tlhip_reg_mask
thip = self.tlhip_mask
T = self.Tl
elif hemi == 'right':
if self.trhip_reg_mask != None:
return self.trhip_reg_mask
thip = self.trhip_mask
T = self.Tr
else:
raise ValueError('neither left nor right!')
tmp = nb.Nifti1Image(thip.astype(float), self.timg.get_affine())
tmp = nr.resample(tmp, T.inv(), reference=self.img, interp_order=1).get_data()
if hemi == 'left':
self.tlhip_reg_mask = tmp.copy()
elif hemi == 'right':
self.trhip_reg_mask = tmp.copy()
return tmp
import nireg as nr
from nidata.task.poldrack_etal_2001 import PoldrackEtal2001Dataset
from nilearn.plotting import plot_stat_map
from nipy.labs.viz import cm
pold_dataset = PoldrackEtal2001Dataset()
data_dict = pold_dataset.fetch(preprocess_data=True)
print(data_dict['anat'][0:2])
print(data_dict['func'][0:2])
func = nb.load(data_dict['func'][0])
anat = nb.load(data_dict['anat'][0])
reg = nr.HistogramRegistration(func, anat)
trns = reg.optimize('rigid')
func_trans = nr.resample(func, trns.inv(), reference=anat)
fh = plt.figure()
plot_stat_map(func,
cmap=cm.hot_black_bone,
black_bg=True,
vmax=100.,
alpha=0.9,
title='Before rigid registration',
bg_img=anat,
axes=fh.add_subplot(2, 1, 1))
plot_stat_map(func_trans,
cmap=cm.hot_black_bone,
black_bg=True,
vmax=100.,
alpha=0.9,
import nireg as nr
from nidata.task.poldrack_etal_2001 import PoldrackEtal2001Dataset
from nilearn.plotting import plot_stat_map
from nipy.labs.viz import cm
pold_dataset = PoldrackEtal2001Dataset()
data_dict = pold_dataset.fetch(preprocess_data=True)
print(data_dict['anat'][0:2])
print(data_dict['func'][0:2])
func = nb.load(data_dict['func'][0])
anat = nb.load(data_dict['anat'][0])
reg = nr.HistogramRegistration(func, anat)
trns = reg.optimize('rigid')
func_trans = nr.resample(func, trns.inv(), reference=anat)
fh = plt.figure()
plot_stat_map(func,
cmap=cm.hot_black_bone,
black_bg=True,
vmax=100., alpha=0.9,
title='Before rigid registration',
bg_img=anat,
axes=fh.add_subplot(2, 1, 1))
plot_stat_map(func_trans,
cmap=cm.hot_black_bone,
black_bg=True,
vmax=100., alpha=0.9,
title='After rigid registration',
bg_img=anat,
# Perform affine registration
# The output is an array-like object such that
# np.asarray(T) is a customary 4x4 matrix
print('Setting up registration...')
tic = time.time()
R = HistogramRegistration(I, J, similarity=similarity, interp=interp,
renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer, xtol=tol, ftol=tol)
toc = time.time()
print(' Registration time: %f sec' % (toc - tic))
# Resample source image
print('Resampling source image...')
tic = time.time()
#It = resample2(I, J.coordmap, T.inv(), J.shape)
It = resample(I, T.inv(), reference=J)
toc = time.time()
print(' Resampling time: %f sec' % (toc - tic))
# Save resampled source
outroot = source + '_TO_' + target
outimg = outroot + '.nii.gz'
print ('Saving resampled source in: %s' % outimg)
nb.save(It, outimg)
# Save transformation matrix
"""
outparams = outroot + '.npy'
np.save(outparams, np.asarray(T))
"""
print('Setting up registration...')
tic = time.time()
R = HistogramRegistration(I,
J,
similarity=similarity,
interp=interp,
renormalize=renormalize)
T = R.optimize('affine', optimizer=optimizer, xtol=tol, ftol=tol)
toc = time.time()
print(' Registration time: %f sec' % (toc - tic))
# Resample source image
print('Resampling source image...')
tic = time.time()
#It = resample2(I, J.coordmap, T.inv(), J.shape)
It = resample(I, T.inv(), reference=J)
toc = time.time()
print(' Resampling time: %f sec' % (toc - tic))
# Save resampled source
outroot = source + '_TO_' + target
outimg = outroot + '.nii.gz'
print('Saving resampled source in: %s' % outimg)
nb.save(It, outimg)
# Save transformation matrix
"""
outparams = outroot + '.npy'
np.save(outparams, np.asarray(T))
"""
