def filter_vols():
cr_vol = nib.load(pat.get_path('crop')).get_data()
if len(cr_vol.shape) == 4:
cr_vol = cr_vol[..., 0]
borders_vol = np.where(cr_vol == 1)
x_fr, y_fr, z_fr = map(np.min, borders_vol)
x_to, y_to, z_to = map(np.max, borders_vol)
print x_fr, y_fr, z_fr, x_to, y_to, z_to
for p, d, f in os.walk(pat.get_path('separated')):
for fname in f:
INTENSITY_SIGMA = 40
GAUSSIAN_SIGMA = 1.5
nii_separator.set_header_from(os.path.join(p, fname),
'/home/denest/PERF_volumes/ZAKHAROVA O.A. 13.11.1981/20140610_635/NII/SEPARATED/s004a001_3.nii.gz')
if not os.path.isfile(os.path.join(pat.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))):
bilateral.bilateral(os.path.join(p, fname), output_folder=pat.get_path('filtered'),
sig_i=INTENSITY_SIGMA, sig_g=GAUSSIAN_SIGMA, x_range=[x_fr, x_to],
y_range=[y_fr, y_to], z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(pat.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
for fn in pat.files_in('filtered'):
splited_fname = re.split(r"s|a|_", fn)
print splited_fname
s, a = [int(i) for i in (splited_fname[1], splited_fname[3])]
pat.add_path(fn, 'filtered', s, a, add_to=(pat.get_path('filtered')))
def filter_vols():
for p, d, f in os.walk(pat.get_path('separated')):
for fname in f:
INTENSITY_SIGMA = 40
GAUSSIAN_SIGMA = 1.5
if not os.path.isfile(os.path.join(pat.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))):
print os.path.join(pat.get_path('filtered'),
'%s_I%s_G%s.nii' % (fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
bilateral.bilateral(os.path.join(p, fname), output_folder=pat.get_path('filtered'),
sig_i=INTENSITY_SIGMA, sig_g=GAUSSIAN_SIGMA, x_range=[x_fr, x_to],
y_range=[y_fr, y_to], z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(pat.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
def filter_vols():
cr_vol = nib.load(pat.get_path('crop')).get_data()
if len(cr_vol.shape) == 4:
cr_vol = cr_vol[..., 0]
borders_vol = np.where(cr_vol == 1)
x_fr, y_fr, z_fr = map(np.min, borders_vol)
x_to, y_to, z_to = map(np.max, borders_vol)
print x_fr, y_fr, z_fr, x_to, y_to, z_to
for p, d, f in os.walk(pat.get_path('separated')):
for fname in f:
INTENSITY_SIGMA = 40
GAUSSIAN_SIGMA = 1.5
nii_separator.set_header_from(
os.path.join(p, fname),
'/home/denest/PERF_volumes/ZAKHAROVA O.A. 13.11.1981/20140610_635/NII/SEPARATED/s004a001_3.nii.gz'
)
if not os.path.isfile(
os.path.join(
pat.get_path('filtered'), '%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), INTENSITY_SIGMA,
GAUSSIAN_SIGMA))):
bilateral.bilateral(os.path.join(p, fname),
output_folder=pat.get_path('filtered'),
sig_i=INTENSITY_SIGMA,
sig_g=GAUSSIAN_SIGMA,
x_range=[x_fr, x_to],
y_range=[y_fr, y_to],
z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(
pat.get_path('filtered'), '%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
for fn in pat.files_in('filtered'):
splited_fname = re.split(r"s|a|_", fn)
print splited_fname
s, a = [int(i) for i in (splited_fname[1], splited_fname[3])]
pat.add_path(fn, 'filtered', s, a, add_to=(pat.get_path('filtered')))
def filter_vols(self, intensity_sigma=40, gaussian_sigma=1.5):
cr_vol = nib.load(self.dir_manager.get_path('crop')).get_data()
if len(cr_vol.shape) == 4:
cr_vol = cr_vol[..., 0]
borders_vol = np.where(cr_vol == 1)
x_fr, y_fr, z_fr = map(np.min, borders_vol)
x_to, y_to, z_to = map(np.max, borders_vol)
for p, d, f in os.walk(self.dir_manager.get_path('separated')):
for fname in f:
if not os.path.isfile(os.path.join(self.dir_manager.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), intensity_sigma, gaussian_sigma))):
# nii_separator.set_header_from(os.path.join(p, fname),
# '/home/denest/PERF_volumes/ZAKHAROVA O.A. 13.11.1981/20140610_635/NII/SEPARATED/s004a001_3.nii.gz')
bilateral.bilateral(os.path.join(p, fname), output_folder=self.dir_manager.get_path('filtered'),
sig_i=intensity_sigma, sig_g=gaussian_sigma, x_range=[x_fr, x_to],
y_range=[y_fr, y_to], z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(self.dir_manager.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), intensity_sigma, gaussian_sigma))
def filter_vols():
for p, d, f in os.walk(pat.get_path('separated')):
for fname in f:
INTENSITY_SIGMA = 40
GAUSSIAN_SIGMA = 1.5
if not os.path.isfile(
os.path.join(
pat.get_path('filtered'), '%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), INTENSITY_SIGMA,
GAUSSIAN_SIGMA))):
print os.path.join(
pat.get_path('filtered'), '%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
bilateral.bilateral(os.path.join(p, fname),
output_folder=pat.get_path('filtered'),
sig_i=INTENSITY_SIGMA,
sig_g=GAUSSIAN_SIGMA,
x_range=[x_fr, x_to],
y_range=[y_fr, y_to],
z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(
pat.get_path('filtered'), '%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), INTENSITY_SIGMA, GAUSSIAN_SIGMA))
for p, d, f in os.walk(self.dir_manager.get_path('separated')):
for fname in f:
if not os.path.isfile(
os.path.join(
self.dir_manager.get_path('filtered'),
'%s_I%s_G%s.nii' %
(fname.rstrip('.nii.gz'), intensity_sigma,
gaussian_sigma))):
# nii_separator.set_header_from(os.path.join(p, fname),
# '/home/denest/PERF_volumes/ZAKHAROVA O.A. 13.11.1981/20140610_635/NII/SEPARATED/s004a001_3.nii.gz')
bilateral.bilateral(
os.path.join(p, fname),
output_folder=self.dir_manager.get_path('filtered'),
sig_i=intensity_sigma,
sig_g=gaussian_sigma,
x_range=[x_fr, x_to],
y_range=[y_fr, y_to],
z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(
self.dir_manager.get_path('filtered'),
'%s_I%s_G%s.nii' % (fname.rstrip('.nii.gz'),
intensity_sigma, gaussian_sigma))
def registration_start(self, target_phase, phase_exclusion=()):
ants = self.ants
# registration
def registration(moved_image, fixed_image, mask, output_folder):
def RSE(m, r):
return math.sqrt(np.square(m - r).sum())
filename = str(input()).rstrip()
img = imageio.imread(filename).astype(np.float)
method = int(input())
save = int(input())
if method == 1:
n = int(input())
sigma_s = float(input())
sigma_r = float(input())
output_img = bilateral(img, n, sigma_s, sigma_r)
elif method == 2:
c = float(input())
k = int(input())
output_img = unsharp(img, c, k)
elif method == 3:
sigma_row = float(input())
sigma_col = float(input())
output_img = vinagrette(img, sigma_row, sigma_col)
else:
raise Exception("Method " + str(method) + " unimplemented")
output_img = output_img.astype(np.uint8)
print("{0:.4f}".format(RSE(output_img, img)))
except IOError,s:
print 'no crop volume',s
x_fr, y_fr, z_fr = (None,None,None)
x_to, y_to, z_to = (None,None,None)
for p, d, f in os.walk(self.dir_manager.get_path('separated')):
for fname in f:
if not os.path.isfile(os.path.join(self.dir_manager.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), intensity_sigma, gaussian_sigma))):
# nii_separator.set_header_from(os.path.join(p, fname),
# '/home/denest/PERF_volumes/ZAKHAROVA O.A. 13.11.1981/20140610_635/NII/SEPARATED/s004a001_3.nii.gz')
bilateral.bilateral(os.path.join(p, fname), output_folder=self.dir_manager.get_path('filtered'),
sig_i=intensity_sigma, sig_g=gaussian_sigma, x_range=[x_fr, x_to],
y_range=[y_fr, y_to], z_range=[z_fr, z_to])
else:
print 'exists', os.path.join(self.dir_manager.get_path('filtered'), '%s_I%s_G%s.nii' % (
fname.rstrip('.nii.gz'), intensity_sigma, gaussian_sigma))
def registration_start(self, target_phase, phase_exclusion=()):
ants = self.ants
# registration
def registration(moved_image, fixed_image, mask, output_folder):
prefix = '%s_to_%s' % (
os.path.basename(moved_image).split('.')[0], os.path.basename(fixed_image).split('.')[0])