def main():
args = parse_args()
logging.basicConfig(level=logging.getLevelName(args.debug_level.upper()))
pybids_cache_path = os.path.join(args.bids_path, PYBIDS_CACHE_PATH)
layout = bids.BIDSLayout(
args.bids_path,
database_path=pybids_cache_path,
reset_database=args.force_reindex,
index_metadata=False,
validate=False,
)
if args.datalad:
annex_repo = AnnexRepo(args.bids_path)
subject_list = (
args.participant_label if args.participant_label else bids.layout.Query.ANY
)
session_list = args.session_label if args.session_label else bids.layout.Query.ANY
filters = dict(
subject=subject_list,
session=session_list,
**args.ref_bids_filters,
extension=['nii','nii.gz'])
deface_ref_images = layout.get(**filters)
if not len(deface_ref_images):
logging.info(f"no reference image found with condition {filters}")
return
new_files, modified_files = [], []
script_dir = os.path.dirname(__file__)
mni_path = os.path.abspath(os.path.join(script_dir, MNI_PATH))
mni_mask_path = os.path.abspath(os.path.join(script_dir, MNI_MASK_PATH))
# if the MNI template image is not available locally
if not os.path.exists(os.path.realpath(mni_path)):
datalad.api.get(mni_path, dataset=datalad.api.Dataset(script_dir + "/../../"))
tmpl_image = nb.load(mni_path)
tmpl_image_mask = nb.load(mni_mask_path)
tmpl_defacemask = generate_deface_ear_mask(tmpl_image)
brain_xtractor = Extractor()
for ref_image in deface_ref_images:
subject = ref_image.entities["subject"]
session = ref_image.entities["session"]
datalad.api.get(ref_image.path)
ref_image_nb = ref_image.get_image()
matrix_path = ref_image.path.replace(
"_%s.%s" % (ref_image.entities["suffix"], ref_image.entities["extension"]),
"_mod-%s_defacemaskreg.mat" % ref_image.entities["suffix"],
)
if os.path.exists(matrix_path):
logging.info("reusing existing registration matrix")
ref2tpl_affine = AffineMap(np.loadtxt(matrix_path))
else:
logging.info(f"running registration of reference serie: {ref_image.path}")
brain_mask = (brain_xtractor.run(ref_image_nb.get_fdata()) > 0.99).astype(
np.uint8
)
brain_mask[:] = scipy.ndimage.morphology.binary_dilation(
brain_mask, iterations=4
)
brain_mask_nb = nb.Nifti1Image(brain_mask, ref_image_nb.affine)
ref2tpl_affine = registration(
tmpl_image, ref_image_nb, tmpl_image_mask, brain_mask_nb
)
np.savetxt(matrix_path, ref2tpl_affine.affine)
new_files.append(matrix_path)
if args.debug_images:
output_debug_images(tmpl_image, ref_image, ref2tpl_affine)
series_to_deface = []
for filters in args.other_bids_filters:
series_to_deface.extend(
layout.get(
extension=["nii", "nii.gz"],
subject=subject,
session=session,
**filters,
)
)
# unlock before making any change to avoid unwanted save
if args.datalad:
annex_repo.unlock([serie.path for serie in series_to_deface])
for serie in series_to_deface:
if args.datalad:
if (
next(annex_repo.get_metadata(serie.path))[1].get(
"distribution-restrictions"
)
is None
):
logging.info(
f"skip {serie.path} as there are no distribution restrictions metadata set."
)
continue
logging.info(f"defacing {serie.path}")
datalad.api.get(serie.path)
serie_nb = serie.get_image()
warped_mask = warp_mask(tmpl_defacemask, serie_nb, ref2tpl_affine)
if args.save_all_masks or serie == ref_image:
warped_mask_path = serie.path.replace(
"_%s" % serie.entities["suffix"],
"_mod-%s_defacemask" % serie.entities["suffix"],
)
if os.path.exists(warped_mask_path):
logging.warning(
f"{warped_mask_path} already exists : will not overwrite, clean before rerun"
)
else:
warped_mask.to_filename(warped_mask_path)
new_files.append(warped_mask_path)
masked_serie = nb.Nifti1Image(
np.asanyarray(serie_nb.dataobj) * np.asanyarray(warped_mask.dataobj),
serie_nb.affine,
serie_nb.header,
)
masked_serie.to_filename(serie.path)
modified_files.append(serie.path)
if args.datalad and len(modified_files):
logging.info("saving files and metadata changes in datalad")
annex_repo.set_metadata(
modified_files, remove={"distribution-restrictions": "sensitive"}
)
datalad.api.save(
modified_files + new_files,
message="deface %d series/images and update distribution-restrictions"
% len(modified_files),
)
