def convert_rest_dicoms_to_mgz(subject, rest_fol):
output_fname = op.join(FMRI_DIR, subject, '{}_rest.mgz'.format(subject))
if op.isfile(output_fname):
return output_fname
dicom_files = glob.glob(op.join(rest_fol, 'MR*'))
dicom_files.sort(key=op.getmtime)
fu.mri_convert(dicom_files[0], output_fname)
if op.isfile(output_fname):
return output_fname
else:
raise Exception('Can\'t find {}!'.format(output_fname))
def convert_ct_to_mgz(subject,
ct_raw_input_fol,
ct_fol='',
output_name='ct_org.mgz',
overwrite=False,
print_only=False,
ask_before=False):
if not op.isdir(ct_fol):
ct_fol = utils.make_dir(op.join(MMVT_DIR, subject, 'ct'))
if op.isfile(op.join(ct_fol, 'ct_reg_to_mr.mgz')) and not overwrite:
return True
if op.isfile(op.join(ct_fol, output_name)):
return True
ct_fname = utils.select_one_file(glob.glob(op.join(ct_fol, '*.mgz')))
if op.isfile(ct_fname):
if utils.namebase(ct_fname) != 'ct_org':
utils.make_link(ct_fname, op.join(ct_fol, 'ct_org.mgz'))
return True
output_fname = op.join(ct_fol, output_name)
if op.isfile(output_fname):
if not overwrite:
return True
else:
os.remove(output_fname)
if op.isfile(op.join(SUBJECTS_DIR, subject, 'ct', 'ct.nii.gz')):
ct_files = [op.join(SUBJECTS_DIR, subject, 'ct', 'ct.nii.gz')]
elif op.isfile(op.join(SUBJECTS_DIR, subject, 'mri', 'ct.nii.gz')):
ct_files = [op.join(SUBJECTS_DIR, subject, 'mri', 'ct.nii.gz')]
else:
if not op.isdir(ct_raw_input_fol):
print('{} does not exist!'.format(ct_fol))
return False
ct_files = glob.glob(op.join(ct_raw_input_fol, '*.dcm'))
if len(ct_files) == 0:
sub_folders = [
d for d in glob.glob(op.join(ct_raw_input_fol, '*'))
if op.isdir(d)
]
if len(sub_folders) == 0:
print('Cannot find CT files in {}!'.format(ct_raw_input_fol))
return False
fol = utils.select_one_file(sub_folders, '', 'CT', is_dir=True)
ct_files = glob.glob(op.join(fol, '*.dcm'))
if len(ct_files) == 0:
print('Cannot find CT files in {}!'.format(fol))
return False
ct_files.sort(key=op.getmtime)
if ask_before:
ret = input('convert {} to {}? '.format(ct_files[0], output_fname))
if not au.is_true(ret):
return False
fu.mri_convert(ct_files[0], output_fname, print_only=print_only)
return True if print_only else op.isfile(output_fname)
def convert_rest_dicoms_to_mgz(subject, rest_fol, overwrite=False):
try:
root = utils.make_dir(op.join(FMRI_DIR, subject))
output_fname = op.join(root, '{}_rest.mgz'.format(subject))
if op.isfile(output_fname):
if not overwrite:
return output_fname
if overwrite:
os.remove(output_fname)
dicom_files = glob.glob(op.join(rest_fol, 'MR*'))
dicom_files.sort(key=op.getmtime)
fu.mri_convert(dicom_files[0], output_fname)
if op.isfile(output_fname):
return output_fname
else:
print('Can\'t find {}!'.format(output_fname))
return ''
except:
utils.print_last_error_line()
return ''
def language(args):
# -f language -s nmr01361 --clinical_dir clin_4090354
# -s nmr01353 -f clean_4d_data --fsd sycabs --remote_fmri_dir "/space/megraid/clinical/MEG-MRI/seder/freesurfer" --nconditions 4
if args.clinical_dir == '':
print('You should set the clinical_dir first. Example: clin_4090354')
return
clinical_root_dir = op.join(args.remote_fmri_dir, args.clinical_dir)
if not op.isdir(clinical_root_dir):
print('{} does not exist!'.format(clinical_root_dir))
task = 'sycabs'
fwhm = 6
subject = args.subject[0]
remote_mri_dir = args.remote_clinical_subjects_dir
subject_mri_dir = op.join(remote_mri_dir, subject)
mri_subject_task_dir = utils.make_dir(op.join(subject_mri_dir, task))
clinical_dirs = glob.glob(op.join(clinical_root_dir, '*'))
clinical_dirs = [
d for d in clinical_dirs if utils.namebase(d) != 'mne_dcm'
]
remote_fmri_dir = utils.select_one_file(clinical_dirs)
fmri_fols = sorted(glob.glob(op.join(remote_fmri_dir, '*_SyCAbs')))
par_fol = utils.make_dir(op.join(remote_mri_dir, subject, 'par'))
par_files = glob.glob(op.join(par_fol, '*.par'))
sessions = sorted(
[utils.find_num_in_str(utils.namebase(d))[0] for d in fmri_fols])
# Warning: You first need to put the original ones in the following folder:
if len(par_files) == 0:
print('\n *** Please put the original par files in {} and rerun ***'.
format(op.join(remote_mri_dir, subject, 'par')))
return
par_files.sort(key=lambda x: int(utils.namebase(x).split('_')[-1]))
ret = input('''
Patient: {}
MRI folder: {}
fMRI root folder: {}
fMRI sessions: {}
Session and pars: {}
Do you want to continue (y/n)? '''.format(
subject, subject_mri_dir, remote_fmri_dir,
[utils.namebase(d) for d in fmri_fols],
list(zip([utils.namebase(f) for f in par_files], sessions))))
if not au.is_true(ret):
return
# You need first to run src.preproc.anatomy
if not op.isfile(anat.get_blend_fname(subject, args.atlas)):
args = anat.read_cmd_args(
dict(
subject=subject,
remote_subject_dir=subject_mri_dir,
ignore_missing=True,
))
pu.run_on_subjects(args, anat.main)
# convert the fMRI dicom files to nii
for fmri_fol in fmri_fols:
ses_num = utils.find_num_in_str(utils.namebase(fmri_fol))[0]
ses_files = glob.glob(op.join(fmri_fol, '**', '*.*'), recursive=True)
output_fname = op.join(
utils.make_dir(op.join(mri_subject_task_dir, ses_num)), 'f.nii.gz')
if not op.isfile(output_fname):
fu.mri_convert(ses_files[0], output_fname)
# Convert and arrange the par file
from src.misc.fmri_scripts import convert_par
for par_file, session in zip(par_files, sessions):
fs_par_fname = op.join(mri_subject_task_dir, session,
'{}.par'.format(task))
# if not op.isfile(fs_par_fname):
warnings = convert_par.sycabs(par_file, fs_par_fname)
if warnings != '':
print(
'\n *** Please fix the problems with the par convertion ({}) and rerun ***\n'
.format(par_file))
return
for hemi in utils.HEMIS:
utils.delete_folder_files(
op.join(remote_mri_dir, '{}_sm{}_{}'.format(task, fwhm, hemi)))
# Run the FreeSurfer analysis
args = fmri.read_cmd_args(
dict(subject=subject,
atlas=args.atlas,
function='clean_4d_data',
fsd=task,
fwhm=fwhm,
remote_fmri_dir=remote_mri_dir,
nconditions=4,
ignore_missing=True,
print_only=False,
overwrite_4d_preproc=False))
pu.run_on_subjects(args, fmri.main)
# Load the fMRI results
args = fmri.read_cmd_args(
dict(
subject=subject,
atlas=args.atlas,
function='load_surf_files',
fmri_file_template=op.join(MMVT_DIR, subject, 'fmri',
'words_v_symbols_{hemi}.mgz'),
))
pu.run_on_subjects(args, fmri.main)