def label_fusion(target_path, atlas_img_path_list, atlas_lab_path_list, out_file, probabilities, params_list):
out_dir = os.path.dirname(out_file)
out_name = os.path.basename(out_file).split(os.extsep, 1)[0]
if params_list[0] == 'Joint':
jointfusion_path = os.path.join(os.environ['ANTSPATH'], 'jointfusion')
prob_dir = os.path.join(out_dir, out_name)
prob_path = os.path.join(prob_dir, 'prob%d.nii.gz')
cmdline = [jointfusion_path, '3', '1']
cmdline += ['-g'] + atlas_img_path_list
cmdline += ['-tg', target_path]
cmdline += ['-l'] + atlas_lab_path_list
cmdline += ['-m', 'Joint']
cmdline += [item for sublist in zip(['-rp', '-rs'], params_list[1:]) for item in sublist]
if probabilities:
os.makedirs(prob_dir)
cmdline += ['-p', prob_path]
cmdline += [out_file]
else:
python_path = os.path.join(os.environ['HOME'], 'anaconda', 'envs', 'sitkpy', 'bin', 'python')
mod_path = os.path.join(os.environ['HOME'], 'CODE', 'mod_py')
nlwv_path = os.path.join(mod_path, 'pblf_py.py')
cmdline = [python_path, '-u', nlwv_path]
cmdline += ['--atlas_img_list'] + atlas_img_path_list
cmdline += ['--target_img', target_path]
cmdline += ['--atlas_lab_list'] + atlas_lab_path_list
cmdline += ['--method'] + params_list[:2]
cmdline += [item for sublist in zip(['--patch_radius', '--search_radius', '--fusion_radius', '--struct_sim', '--normalization',], params_list[2:]) for item in sublist]
if probabilities:
cmdline += ['--probabilities']
cmdline += ['--out_file', out_file]
# launch
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = "{}_joint".format(out_name)
qsub_launcher.folder = out_dir
# qsub_launcher.queue = 'short.q'
qsub_launcher.queue = 'default.q'
return qsub_launcher.run()
type=int,
nargs=1,
default=[8],
help='number of concurrent processes ')
parser.add_argument("--num_itk_threads",
type=int,
nargs=1,
default=[1],
help='number of threads per ANTs proc ')
args = parser.parse_args()
# args = parser.parse_args('--in_dir /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk --img_suffix moving.nii.gz --template_file /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk/fixed.nii.gz --transform Affine 4 --out_warp_intfix rigid3 --out_dir /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk --init_warp_dir_suffix /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk moving_warped0GenericAffine.mat --init_warp_dir_suffix /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk moving_masked_warped20GenericAffine.mat 1 --template_mask /Users/gsanroma/DATA/DATABASES/ADNI/atlases/kk/left2.nii.gz'.split())
from scheduler import Launcher
launcher = Launcher(args.num_procs[0])
# default num of iterations
ITS_LINEAR = [
'%d' % int(500 / args.speedup[0]),
'%d' % int(250 / args.speedup[0]),
'%d' % int(125 / args.speedup[0]),
'%d' % int(50 / args.speedup[0])
]
ITS_SYN = [
'%d' % int(70 / args.speedup[0]),
'%d' % int(50 / args.speedup[0]),
'%d' % int(30 / args.speedup[0]),
'%d' % int(10 / args.speedup[0])
]
args.reg_dir[0], file_name + args.in_deform_intfix[0] +
'1InverseWarp.nii.gz')
]
cmdline += [
'--output',
os.path.join(args.out_dir[0],
file.split('.nii.gz')[0] + args.out_suffix[0])
]
#
# launch
print "Launching warping of file {}".format(file)
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = file.split('.nii.gz')[0]
qsub_launcher.folder = args.out_dir[0]
qsub_launcher.queue = 'short.q'
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
# Wait for the jobs to finish (in cluster)
if is_hpc:
print "Waiting for warping jobs to finish..."
call(wait_jobs)
print "Warping finished."
# print('FOUND: %s' % [os.path.exists(os.path.join(args.gtr_dir[0], f)) for f in gtr_files])
assert not False in [
os.path.exists(os.path.join(args.gtr_dir[0], f)) for f in gtr_files
], "Some ground-truth segmentations not found"
Nimg = len(est_files)
# temp directory
tmp_dir = os.path.join(args.est_dir[0], 'tmp')
if os.path.exists(tmp_dir):
rmtree(tmp_dir)
os.makedirs(tmp_dir)
imagemath_path = os.path.join(os.environ['ANTSPATH'], 'ImageMath')
launcher = Launcher(args.num_procs[0])
out_paths = []
for i_img in range(Nimg):
est_path = os.path.join(args.est_dir[0], est_files[i_img])
gtr_path = os.path.join(args.gtr_dir[0], gtr_files[i_img])
out_path = os.path.join(tmp_dir, est_names[i_img])
out_paths.append(out_path)
cmdline = "%s 3 %s DiceAndMinDistSum %s %s" % (imagemath_path, out_path,
est_path, gtr_path)
qsub_launcher = Launcher(cmdline)
cmdline += ['--float', '1']
#
# mask
if args.template_mask is not None:
cmdline += ['--masks', args.template_mask[0]]
#
# launch
print("Launching registration of file {}".format(mat_file))
# os.system(' '.join(cmdline))
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = mat_file.split(os.extsep, 1)[0]
qsub_launcher.folder = args.out_dir[0]
# qsub_launcher.omp_num_threads = args.num_threads[0]
qsub_launcher.queue = 'short'
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
n_jobs += 1
# Wait for the jobs to finish (in cluster)
if is_hpc and n_total_jobs <= n_jobs:
print("Waiting for registration jobs to finish...")
call(wait_jobs)
imagemath_path, '3',
os.path.join(tmp_dir, 'dummy.txt'), 'NormalizedCorrelation'
]
cmdline += [
os.path.join(in_dir, in_files_list[i]),
os.path.join(in2_dir, in2_files_list[i2])
]
if args.mask_file is not None:
cmdline += [
os.path.join(tmp_dir,
os.path.basename(args.mask_file[0]))
]
job_name = "{0}X{1}".format(RID_1 + '_' + sampleid_1,
RID_2 + '_' + sampleid_2)
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = job_name
qsub_launcher.folder = tmp_dir
qsub_launcher.queue = "short.q"
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
n_jobs += 1
list_of_jobs.append((job_name, i, i2))
# Wait for the jobs to finish (in cluster)
if is_hpc and n_total_jobs <= n_jobs:
print("Waiting for registration jobs to finish...")
call(wait_jobs)
'--input', '{}{}'.format(os.path.join(args.in_dir[0], img_name),
args.img_suffix[0])
]
cmdline += ['--input-image-type', '3']
cmdline += ['--interpolation', 'Linear']
cmdline += [
'--reference-image', '{}'.format(os.path.join(args.template_dir[0]))
]
cmdline += ['--transform', '{}'.format(os.path.join(args.matrix[0]))]
# launch
print("Launching registration of file {}".format(img_file))
# os.system(' '.join(cmdline))
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = img_file.split(os.extsep, 1)[0]
qsub_launcher.folder = args.out_dir[0]
#qsub_launcher.omp_num_threads = args.num_threads[0]
# qsub_launcher.queue = 'short.q'
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
n_jobs += 1
# Wait for the jobs to finish (in cluster)
if is_hpc and n_total_jobs <= n_jobs:
print("Waiting for registration jobs to finish...")
call(wait_jobs)
# the output.
out_path = img_file.replace(in_dir, args.out_dir[0])
if not os.path.exists(os.path.dirname(out_path)):
os.makedirs(os.path.dirname(out_path))
cmdline = [n4_path, '--image-dimensionality', '3']
cmdline += ['--input-image', img_file]
cmdline += ['--shrink-factor', '3']
cmdline += ['--convergence', '50x50x30x20', '1e-6']
cmdline += ['--bspline-fitting', '300']
cmdline += ['--output', out_path]
print("Launching N4 for {}".format(img_file))
qsub_launcher = Launcher(' '.join(cmdline))
qsub_launcher.name = os.path.splitext(os.path.basename(img_file))[0]
qsub_launcher.folder = os.path.dirname(out_path)
qsub_launcher.queue = 'short'
job_id = qsub_launcher.run()
njobs = njobs + 1
if is_hpc:
wait_jobs += [job_id]
if is_hpc and njobs >= n_total_jobs:
print("Limit found. Wait for jobs to finish...")
call(wait_jobs)
njobs = 0
wait_jobs = [
os.path.join(os.environ['ANTSSCRIPTS'], "waitForSlurmJobs.pl"),
'0', '10'
'10'
]
out_paths = []
for i_img in range(Nimg):
est_path = os.path.join(est_dir[0], est_files[i_img])
gtr_path = os.path.join(args.gtr_dir[0], gtr_files[i_img])
out_path = os.path.join(tmp_dir, est_names[i_img])
out_paths += [out_path]
cmdline = "{} 3 {} DiceAndMinDistSum {} {}\n".format(
imagemath_path, out_path, est_path, gtr_path)
qsub_launcher = Launcher(cmdline)
print "Launching Dice evaluation job for labels {}".format(
est_names[i_img])
qsub_launcher.name = est_names[i_img]
qsub_launcher.folder = tmp_dir
qsub_launcher.queue = 'short.q'
job_id = qsub_launcher.run()
if is_hpc:
wait_jobs += [job_id]
if is_hpc:
print "Waiting for Dice evaluation jobs to finish..."
subprocess.call(wait_jobs)
f for f in atlas_files_list if f.endswith(args.atlas_linear_suffix[i][0])
] for i in range(len(args.atlas_linear_suffix))]
atlas_nearest_superlist = [[
f for f in atlas_files_list if f.endswith(args.atlas_nearest_suffix[i][0])
] for i in range(len(args.atlas_nearest_suffix))]
# create output directory
if not os.path.exists(args.out_dir[0]):
os.makedirs(args.out_dir[0])
if not args.inverse:
print "Warping each atlas to target"
else:
print "Warping target to each atlas"
launcher = Launcher(args.num_procs[0])
antsapplytransforms_path = os.path.join(os.environ['ANTSPATH'],
'antsApplyTransforms')
target_name = os.path.basename(args.target_file[0]).split(
args.target_suffix[0])[0]
for atlas_files_list, suffix, interpolation in zip(atlas_linear_superlist, args.atlas_linear_suffix, ['Linear']*len(args.atlas_linear_suffix)) + \
zip(atlas_nearest_superlist, args.atlas_nearest_suffix, ['NearestNeighbor']*len(args.atlas_nearest_suffix)):
for atlas_file in atlas_files_list:
cmdline = [antsapplytransforms_path, '--dimensionality', '3']
cmdline += ['--interpolation', interpolation]
cmdline += ['--default-value', '0']