def wrapper_multiprocessing(self, fileIDs, subjects, modality):
"""To avoid redundancy between CT and MR registration to common space, this part is wrapped up here """
working_dir = self.cfg['folders']['nifti']
prefix = '{}2template'.format(modality)
# Start multiprocessing framework
start_multi = time.time()
status = mp.Queue()
processes = [
mp.Process(target=self.ANTsCoregisterMultiprocessing,
args=(filename_fixed, filename_moving, no_subj,
os.path.join(working_dir, no_subj),
'registration', prefix, status))
for filename_fixed, filename_moving, no_subj in fileIDs
]
for p in processes:
p.start()
while any([p.is_alive() for p in processes]):
while not status.empty():
filename_fixed, filename_moving, no_subj = status.get()
print("\tRegistering {} (f) to {} (m), in ANTsPy\n".format(
filename_fixed,
os.path.split(filename_moving)[1], no_subj))
time.sleep(0.1)
for p in processes:
p.join()
# Functions creating/updating pipeline log, which documents all steps along with settings
for subjID in subjects:
files_processed = [(os.path.split(file_moving)[1],
os.path.split(file_fixed)[1])
for file_fixed, file_moving, subj_no in fileIDs
if subj_no == subjID]
log_text = "{} successfully registered (@{}) to \n{}, \n\n Mean Duration per subject: {:.2f} " \
"secs".format(files_processed[0][0], time.strftime("%Y%m%d-%H%M%S"), files_processed[0][1],
(time.time() - start_multi) / len(subjects))
Output.logging_routine(text=Output.split_lines(log_text),
cfg=self.cfg,
subject=str(subjID),
module='{}-Registration'.format(modality),
opt=self.cfg['preprocess']['registration'],
project="")
print(
'\nIn total, a list of {} subject(s) was processed; {} registration took {:.2f}secs. '
'overall'.format(len(subjects), modality,
time.time() - start_multi))
def dcm2niix_multiprocessing(self, name_subj, no_subj, dcm2niix_bin,
last_idx, total_subj, status):
"""function intended to provide multiprocessing approach to speed up extraction of DICOM data to nifti files"""
modalities = ['CT', 'MRI']
if self.logfile:
log_filename = os.path.join(
ROOTDIR, 'logs', 'log_DCM2NII_' + str(no_subj + last_idx) +
time.strftime("%Y%m%d-%H%M%S"))
else:
log_filename = os.devnull
subj_outdir = os.path.join(
self.outdir,
self.cfg['folders']['prefix'] + str(no_subj + last_idx))
FileOperations.create_folder(subj_outdir)
start_time_subject = time.time()
keptfiles, deletedfiles = ([] for _ in range(2))
for mod in modalities:
status.put((name_subj, mod, no_subj, total_subj))
input_folder_name = os.path.join(self.inputdir, name_subj + mod)
# input_folder_files = [f.path for f in os.scandir(input_folder_name)
# if (f.is_dir() and ('100' in f.path or 'DICOM' in f.path or '001' in f.path))]
input_folder_files = []
[
input_folder_files.append(item)
for item in os.listdir(input_folder_name)
if (os.path.isdir(os.path.join(input_folder_name, item)) and (
'100' in item or 'DICOM' in item or '001' in item))
]
orig_stdout = sys.stdout
sys.stdout = open(log_filename, 'w')
for folder in input_folder_files:
subprocess.call(
[
dcm2niix_bin,
'-a',
'y', # anonimisation of DICOM data
'-b',
self.cfg['preprocess']['dcm2nii']['BIDSsidecar'][0],
'-z',
self.cfg['preprocess']['dcm2nii']['OutputCompression']
[0],
'-f',
self.cfg['preprocess']['dcm2nii']['OutputFileStruct'],
'-o',
subj_outdir,
'-w',
str(self.cfg['preprocess']['dcm2nii']
['NameConflicts']),
'-v',
str(self.cfg['preprocess']['dcm2nii']['Verbosity']),
'-x',
str(self.cfg['preprocess']['dcm2nii']['ReorientCrop']),
folder
],
stdout=sys.stdout,
stderr=subprocess.STDOUT)
sys.stdout.close()
sys.stdout = orig_stdout
files_kept, files_deleted = self.select_sequences(subj_outdir)
keptfiles.extend(files_kept)
deletedfiles.extend(files_deleted)
# Functions creating/updating pipeline log, which document individually all steps along with settings
log_text = "{} files successfully converted: {}, \n\nand {} deleted: {}.\nDuration: {:.2f} secs" \
.format(len(set(keptfiles)),
'\n\t{}'.format('\n\t'.join(os.path.split(x)[1] for x in sorted(set(keptfiles)))),
len(set(deletedfiles)),
'\n\t{}'.format('\n\t'.join(os.path.split(x)[1] for x in sorted(set(deletedfiles)))),
time.time() - start_time_subject)
Output.logging_routine(text=Output.split_lines(log_text),
cfg=self.cfg,
subject=self.cfg['folders']['prefix'] +
str(no_subj),
module='dcm2nii',
opt=self.cfg['preprocess']['dcm2nii'],
project="")
def N4BiasCorrection(self, subjects):
"""N4BiasCorrection according to N.J. Tustison, ..., and J.C. Gee.
"N4ITK: Improved N3 Bias Correction" IEEE Transactions on Medical Imaging, 29(6):1310-1320, June 2010."""
print('\nDebiasing imaging of {} subject(s)'.format(len(subjects)))
allfiles = FileOperations.get_filelist_as_tuple(inputdir=self.cfg['folders']['nifti'], subjects=subjects)
strings2exclude = ['CT', self.cfg['preprocess']['ANTsN4']['prefix'], 'reg_run', 'Mask', 'Warp', 'Registration']
allfiles = [x for x in allfiles if x[0].endswith('.nii') and not
any(re.search(r'\w+(?!_).({})|^({})\w+.'.format(z, z), os.path.basename(x[0]), re.IGNORECASE)
for z in strings2exclude)]
file_id_DTI = [x for x in allfiles if (x[0].endswith('.nii') and self.cfg['preprocess']['ANTsN4']['dti_prefix']
in x[0]) and not
any(re.search(r'\w+(?!_).({})|^({})\w+.'.format(z, z), os.path.basename(x[0]), re.IGNORECASE)
for z in strings2exclude)]
file_id_noDTI = [x for x in allfiles if (x[0].endswith('.nii') and not
self.cfg['preprocess']['ANTsN4']['dti_prefix'] in x[0]) and not
any(re.search(r'\w+(?!_).({})|^({})\w+.'.format(z, z), os.path.basename(x[0]), re.IGNORECASE)
for z in strings2exclude)]
seq = 'struct' # For debugging purposes
if not seq:
fileIDs = allfiles
elif seq == 'struct':
fileIDs = list(set(allfiles) - set(file_id_DTI))
elif seq == 'dwi':
fileIDs = list(set(allfiles) - set(file_id_noDTI))
start_multi = time.time()
status = mp.Queue()
processes = [mp.Process(target=self.N4BiasCorrection_multiprocessing,
args=(name_file, no_subj, os.path.join(self.cfg['folders']['nifti'], no_subj), status))
for name_file, no_subj in fileIDs]
for p in processes:
p.start()
while any([p.is_alive() for p in processes]):
while not status.empty():
process, no_subj, filename = status.get()
print("Process: {}; Debiasing {}, filename: {}".format(process, no_subj, filename))
time.sleep(0.1)
for p in processes:
p.join()
# Functions creating/updating pipeline log, which document individually all steps along with settings
for subjID in subjects:
allfiles_subj = [os.path.split(files_subj)[1] for files_subj, subj_no in fileIDs if subj_no == subjID]
log_text = "{} files successfully processed (@{}): {}, \n\n Mean Duration per subject: {:.2f} secs" \
.format(len(set(allfiles_subj)), time.strftime("%Y%m%d-%H%M%S"),
'\n\t{}'.format('\n\t'.join(os.path.split(x)[1] for x in sorted(set(allfiles_subj)))),
(time.time() - start_multi) / len(subjects))
Output.logging_routine(text=Output.split_lines(log_text), cfg=self.cfg,
subject=str(subjID), module='N4BiasCorrection',
opt=self.cfg['preprocess']['ANTsN4'], project="")
print('\nIn total, a list of {} subject(s) was processed \nOverall, bias correction took '
'{:.1f} secs.'.format(len(subjects), time.time() - start_multi))