def main():
parser = buildArgsParser()
args = parser.parse_args()
param = {}
if args.pft_theta is None and args.pft_curvature is None:
args.pft_theta = 20
if not np.any([args.nt, args.npv, args.ns]):
args.npv = 1
if args.theta is not None:
theta = gm.math.radians(args.theta)
elif args.curvature > 0:
theta = get_max_angle_from_curvature(args.curvature, args.step_size)
elif args.algo == 'prob':
theta = gm.math.radians(20)
else:
theta = gm.math.radians(45)
if args.pft_curvature is not None:
pft_theta = get_max_angle_from_curvature(args.pft_curvature, args.step_size)
else:
pft_theta = gm.math.radians(args.pft_theta)
if args.mask_interp == 'nn':
mask_interpolation = 'nearest'
elif args.mask_interp == 'tl':
mask_interpolation = 'trilinear'
else:
parser.error("--mask_interp has wrong value. See the help (-h).")
return
if args.field_interp == 'nn':
field_interpolation = 'nearest'
elif args.field_interp == 'tl':
field_interpolation = 'trilinear'
else:
parser.error("--sh_interp has wrong value. See the help (-h).")
return
param['random'] = args.random
param['skip'] = args.skip
param['algo'] = args.algo
param['mask_interp'] = mask_interpolation
param['field_interp'] = field_interpolation
param['theta'] = theta
param['sf_threshold'] = args.sf_threshold
param['pft_sf_threshold'] = args.pft_sf_threshold if args.pft_sf_threshold is not None else args.sf_threshold
param['sf_threshold_init'] = args.sf_threshold_init
param['step_size'] = args.step_size
param['max_length'] = args.max_length
param['min_length'] = args.min_length
param['is_single_direction'] = args.is_single_direction
param['nbr_seeds'] = args.nt if args.nt is not None else 0
param['nbr_seeds_voxel'] = args.npv if args.npv is not None else 0
param['nbr_streamlines'] = args.ns if args.ns is not None else 0
param['max_no_dir'] = int(math.ceil(args.maxL_no_dir / param['step_size']))
param['is_all'] = args.is_all
param['is_act'] = args.is_act
param['theta_pft'] = pft_theta
if args.not_is_pft:
param['nbr_particles'] = 0
param['back_tracking'] = 0
param['front_tracking'] = 0
else:
param['nbr_particles'] = args.nbr_particles
param['back_tracking'] = int(
math.ceil(args.back_tracking / args.step_size))
param['front_tracking'] = int(
math.ceil(args.front_tracking / args.step_size))
param['nbr_iter'] = param['back_tracking'] + param['front_tracking']
param['mmap_mode'] = None if args.isLoadData else 'r'
if args.isVerbose:
logging.basicConfig(level=logging.DEBUG)
logging.debug('Tractography parameters:\n{0}'.format(param))
if os.path.isfile(args.output_file):
if args.isForce:
logging.info('Overwriting "{0}".'.format(args.output_file))
else:
parser.error(
'"{0}" already exists! Use -f to overwrite it.'
.format(args.output_file))
include_dataset = Dataset(
nib.load(args.map_include_file), param['mask_interp'])
exclude_dataset = Dataset(
nib.load(args.map_exclude_file), param['mask_interp'])
if param['is_act']:
mask = ACT(include_dataset, exclude_dataset,
param['step_size'] / include_dataset.size[0])
else:
mask = CMC(include_dataset, exclude_dataset,
param['step_size'] / include_dataset.size[0])
dataset = Dataset(nib.load(args.sh_file), param['field_interp'])
field = SphericalHarmonicField(
dataset, args.basis, param['sf_threshold'],
param['sf_threshold_init'], param['theta'])
if args.algo == 'det':
tracker = deterministicMaximaTracker(field, param['step_size'])
elif args.algo == 'prob':
tracker = probabilisticTracker(field, param['step_size'])
else:
parser.error("--algo has wrong value. See the help (-h).")
return
pft_field = SphericalHarmonicField(
dataset, args.basis, param['pft_sf_threshold'],
param['sf_threshold_init'], param['theta_pft'])
pft_tracker = probabilisticTracker(pft_field, param['step_size'])
# ADD Seed input
# modify ESO
nib_mask = nib.load(args.map_include_file)
seed_points = np.load(args.seed_points)
seed_dirs = np.load(args.seed_dir)
rotation = nib_mask.get_affine()[:3,:3]
inv_rotation = np.linalg.inv(rotation)
translation = nib_mask.get_affine()[:3,3]
scale = np.array(nib_mask.get_header().get_zooms())
voxel_space = nib.aff2axcodes(nib_mask.get_affine())
print voxel_space
# seed points transfo
# LPS -> voxel_space
print scale
if voxel_space[0] != 'L':
print "flip X"
seed_points[:,0] = -seed_points[:,0]
if voxel_space[1] != 'P':
print "flip Y"
seed_points[:,1] = -seed_points[:,1]
if voxel_space[2] != 'S':
print "flip Z"
seed_points[:,2] = -seed_points[:,2]
# other transfo
seed_points = seed_points - translation
seed_points = seed_points.dot(inv_rotation)
seed_points = seed_points * scale
# seed dir transfo
seed_dirs[:,0:2] = -seed_dirs[:,0:2]
seed_dirs = seed_dirs.dot(inv_rotation)
seed_dirs = seed_dirs * scale
if args.inv_seed_dir:
seed_dirs = seed_dirs * -1.0
# Compute tractography
nb_seeds = len(seed_dirs)
if args.test is not None and args.test < nb_seeds:
nb_seeds = args.test
# end modify ESO
# tracker to modify
# modify ESO
start = time.time()
streamlines = []
for i in range(nb_seeds):
s = generate_streamline(tracker, mask, seed_points[i], seed_dirs[i], pft_tracker=pft_tracker, param=param)
streamlines.append(s)
stdout.write("\r %d%%" % (i*101//nb_seeds))
stdout.flush()
stdout.write("\n done")
stdout.flush()
stop = time.time()
# end modify ESO
# ADD save fiber output
# modify ESO
for i in range(len(streamlines)):
streamlines[i] = streamlines[i] / scale
streamlines[i] = streamlines[i].dot(rotation)
streamlines[i] = streamlines[i] + translation
# voxel_space -> LPS
if voxel_space[0] != 'L':
streamlines[i][:,0] = -streamlines[i][:,0]
if voxel_space[1] != 'P':
streamlines[i][:,1] = -streamlines[i][:,1]
if voxel_space[2] != 'S':
streamlines[i][:,2] = -streamlines[i][:,2]
lines_polydata = lines_to_vtk_polydata(streamlines, None, np.float32)
save_polydata(lines_polydata, args.output_file , True)
# end modify ESO
lengths = [len(s) for s in streamlines]
if nb_seeds > 0:
ave_length = (sum(lengths) / nb_seeds) * param['step_size']
else:
ave_length = 0
str_ave_length = "%.2f" % ave_length
str_time = "%.2f" % (stop - start)
print(str(nb_seeds) + " streamlines, with an average length of " +
str_ave_length + " mm, done in " + str_time + " seconds.")
def main():
parser = buildArgsParser()
args = parser.parse_args()
param = {}
if args.isVerbose:
logging.basicConfig(level=logging.DEBUG)
if args.outputTQ:
filename_parts = os.path.splitext(args.output_file)
output_filename = filename_parts[0] + '.tq' + filename_parts[1]
else:
output_filename = args.output_file
out_format = tc.detect_format(output_filename)
if out_format not in [tc.formats.trk.TRK, tc.formats.tck.TCK]:
parser.error("Invalid output streamline file format (must be trk or " +
"tck): {0}".format(output_filename))
return
if os.path.isfile(output_filename):
if args.isForce:
logging.debug('Overwriting "{0}".'.format(output_filename))
else:
parser.error(
'"{0}" already exists! Use -f to overwrite it.'.format(
output_filename))
if not args.min_length > 0:
parser.error('minL must be > 0, {0}mm was provided.'.format(
args.min_length))
if args.max_length < args.min_length:
parser.error(
'maxL must be > than minL, (minL={0}mm, maxL={1}mm).'.format(
args.min_length, args.max_length))
if not np.any([args.nt, args.npv, args.ns]):
args.npv = 1
if args.theta is not None:
theta = gm.math.radians(args.theta)
elif args.curvature > 0:
theta = get_max_angle_from_curvature(args.curvature, args.step_size)
else:
theta = gm.math.radians(45)
if args.mask_interp == 'nn':
mask_interpolation = 'nearest'
elif args.mask_interp == 'tl':
mask_interpolation = 'trilinear'
else:
parser.error("--mask_interp has wrong value. See the help (-h).")
return
param['random'] = args.random
param['skip'] = args.skip
param['algo'] = args.algo
param['mask_interp'] = mask_interpolation
param['field_interp'] = 'nearest'
param['theta'] = theta
param['sf_threshold'] = args.sf_threshold
param['sf_threshold_init'] = args.sf_threshold_init
param['step_size'] = args.step_size
param['rk_order'] = args.rk_order
param['max_length'] = args.max_length
param['min_length'] = args.min_length
param['max_nbr_pts'] = int(param['max_length'] / param['step_size'])
param['min_nbr_pts'] = int(param['min_length'] / param['step_size']) + 1
param['is_single_direction'] = args.is_single_direction
param['nbr_seeds'] = args.nt if args.nt is not None else 0
param['nbr_seeds_voxel'] = args.npv if args.npv is not None else 0
param['nbr_streamlines'] = args.ns if args.ns is not None else 0
param['max_no_dir'] = int(math.ceil(args.maxL_no_dir / param['step_size']))
param['is_all'] = False
param['is_keep_single_pts'] = False
# r+ is necessary for interpolation function in cython who
# need read/write right
param['mmap_mode'] = None if args.isLoadData else 'r+'
logging.debug('Tractography parameters:\n{0}'.format(param))
seed_img = nib.load(args.seed_file)
seed = Seed(seed_img)
if args.npv:
param['nbr_seeds'] = len(seed.seeds) * param['nbr_seeds_voxel']
param['skip'] = len(seed.seeds) * param['skip']
if len(seed.seeds) == 0:
parser.error('"{0}" does not have voxels value > 0.'.format(
args.seed_file))
mask = BinaryMask(Dataset(nib.load(args.mask_file), param['mask_interp']))
dataset = Dataset(nib.load(args.peaks_file), param['field_interp'])
field = MaximaField(dataset, param['sf_threshold'],
param['sf_threshold_init'], param['theta'])
if args.algo == 'det':
tracker = deterministicMaximaTracker(field, param)
elif args.algo == 'prob':
tracker = probabilisticTracker(field, param)
else:
parser.error("--algo has wrong value. See the help (-h).")
return
start = time.time()
if args.compress:
if args.compress < 0.001 or args.compress > 1:
logging.warn(
'You are using an error rate of {}.\n'.format(args.compress) +
'We recommend setting it between 0.001 and 1.\n' +
'0.001 will do almost nothing to the tracts while ' +
'1 will higly compress/linearize the tracts')
streamlines = track(tracker,
mask,
seed,
param,
compress=True,
compression_error_threshold=args.compress,
nbr_processes=args.nbr_processes,
pft_tracker=None)
else:
streamlines = track(tracker,
mask,
seed,
param,
nbr_processes=args.nbr_processes,
pft_tracker=None)
if args.outputTQ:
save_streamlines_tractquerier(streamlines, args.seed_file,
output_filename)
else:
save_streamlines_fibernavigator(streamlines, args.seed_file,
output_filename)
str_ave_length = "%.2f" % compute_average_streamlines_length(streamlines)
str_time = "%.2f" % (time.time() - start)
logging.debug(
str(len(streamlines)) + " streamlines, with an average " +
"length of " + str_ave_length + " mm, done in " + str_time +
" seconds.")
def main():
np.random.seed(int(time.time()))
parser = buildArgsParser()
args = parser.parse_args()
param = {}
if args.algo not in ["det", "prob"]:
parser.error("--algo has wrong value. See the help (-h).")
if args.basis not in ["mrtrix", "dipy", "fibernav"]:
parser.error("--basis has wrong value. See the help (-h).")
#if np.all([args.nt is None, args.npv is None, args.ns is None]):
# args.npv = 1
if args.theta is not None:
theta = gm.math.radians(args.theta)
elif args.curvature > 0:
theta = get_max_angle_from_curvature(args.curvature, args.step_size)
elif args.algo == 'prob':
theta = gm.math.radians(20)
else:
theta = gm.math.radians(45)
if args.mask_interp == 'nn':
mask_interpolation = 'nearest'
elif args.mask_interp == 'tl':
mask_interpolation = 'trilinear'
else:
parser.error("--mask_interp has wrong value. See the help (-h).")
return
if args.field_interp == 'nn':
field_interpolation = 'nearest'
elif args.field_interp == 'tl':
field_interpolation = 'trilinear'
else:
parser.error("--sh_interp has wrong value. See the help (-h).")
return
param['algo'] = args.algo
param['mask_interp'] = mask_interpolation
param['field_interp'] = field_interpolation
param['theta'] = theta
param['sf_threshold'] = args.sf_threshold
param['sf_threshold_init'] = args.sf_threshold_init
param['step_size'] = args.step_size
param['max_length'] = args.max_length
param['min_length'] = args.min_length
param['is_single_direction'] = False
param['nbr_seeds'] = 0
param['nbr_seeds_voxel'] = 0
param['nbr_streamlines'] = 0
param['max_no_dir'] = int(math.ceil(args.maxL_no_dir / param['step_size']))
param['is_all'] = False
param['isVerbose'] = args.isVerbose
if param['isVerbose']:
logging.basicConfig(level=logging.DEBUG)
if param['isVerbose']:
logging.info('Tractography parameters:\n{0}'.format(param))
if os.path.isfile(args.output_file):
if args.isForce:
logging.info('Overwriting "{0}".'.format(args.output_file))
else:
parser.error(
'"{0}" already exists! Use -f to overwrite it.'
.format(args.output_file))
nib_mask = nib.load(args.mask_file)
mask = BinaryMask(
Dataset(nib_mask, param['mask_interp']))
dataset = Dataset(nib.load(args.sh_file), param['field_interp'])
field = SphericalHarmonicField(
dataset, args.basis, param['sf_threshold'], param['sf_threshold_init'], param['theta'])
if args.algo == 'det':
tracker = deterministicMaximaTracker(field, param['step_size'])
elif args.algo == 'prob':
tracker = probabilisticTracker(field, param['step_size'])
else:
parser.error("--algo has wrong value. See the help (-h).")
return
start = time.time()
# Etienne St-Onge
#load and transfo *** todo test with rotation and scaling
seed_points = np.load(args.seed_points)
seed_dirs = np.load(args.seed_dir)
rotation = nib_mask.get_affine()[:3,:3]
inv_rotation = np.linalg.inv(rotation)
translation = nib_mask.get_affine()[:3,3]
scale = np.array(nib_mask.get_header().get_zooms())
voxel_space = nib.aff2axcodes(nib_mask.get_affine())
print voxel_space
# seed points transfo
# LPS -> voxel_space
if voxel_space[0] != 'L':
print "flip X"
seed_points[:,0] = -seed_points[:,0]
if voxel_space[1] != 'P':
print "flip Y"
seed_points[:,1] = -seed_points[:,1]
if voxel_space[2] != 'S':
print "flip Z"
seed_points[:,2] = -seed_points[:,2]
# other transfo
seed_points = seed_points - translation
seed_points = seed_points.dot(inv_rotation)
seed_points = seed_points * scale
# seed dir transfo
seed_dirs[:,0:2] = -seed_dirs[:,0:2]
seed_dirs = seed_dirs.dot(inv_rotation)
seed_dirs = seed_dirs * scale
if args.inv_seed_dir:
seed_dirs = seed_dirs * -1.0
# Compute tractography
nb_seeds = len(seed_dirs)
if args.test is not None and args.test < nb_seeds:
nb_seeds = args.test
print args.algo," nb seeds: ", nb_seeds
streamlines = []
for i in range(nb_seeds):
s = generate_streamline(tracker, mask, seed_points[i], seed_dirs[i], pft_tracker=None, param=param)
streamlines.append(s)
stdout.write("\r %d%%" % (i*101//nb_seeds))
stdout.flush()
stdout.write("\n done")
stdout.flush()
# transform back
for i in range(len(streamlines)):
streamlines[i] = streamlines[i] / scale
streamlines[i] = streamlines[i].dot(rotation)
streamlines[i] = streamlines[i] + translation
# voxel_space -> LPS
if voxel_space[0] != 'L':
streamlines[i][:,0] = -streamlines[i][:,0]
if voxel_space[1] != 'P':
streamlines[i][:,1] = -streamlines[i][:,1]
if voxel_space[2] != 'S':
streamlines[i][:,2] = -streamlines[i][:,2]
lines_polydata = lines_to_vtk_polydata(streamlines, None, np.float32)
save_polydata(lines_polydata, args.output_file , True)
lengths = [len(s) for s in streamlines]
if nb_seeds > 0:
ave_length = (sum(lengths) / nb_seeds) * param['step_size']
else:
ave_length = 0
str_ave_length = "%.2f" % ave_length
str_time = "%.2f" % (time.time() - start)
print(str(nb_seeds) + " streamlines, with an average length of " +
str_ave_length + " mm, done in " + str_time + " seconds.")
