def select_grey_matter(fsdir, subjectid, mat_file, outdir, verbose=0):
""" Select only the grey matter using FreeSurfer segmentation.
Parameters
----------
fsdir: str (mandatory)
the freesurfer working directory with all the subjects.
subjectid: str (mandatory)
the subject identifier.
outdir: str (mandatory)
the folder where the computed grey matter mask image will be saved.
verbose: int (optional, default 0)
the verbosity level.
Returns
-------
wm_file: str
a binary segmantation of the white matter.
affine: array (4, 4)
the physical to physical t1 to functional transformation.
"""
# Checks
if not os.path.isdir(outdir):
raise ValueError("'{0}' is not a valid folder.".format(outdir))
# Convert the segmention to the native space
regex = os.path.join(subjectid, "mri", "aseg.mgz")
gm_files = mri_convert(
fsdir, regex, reslice=True, interpolation="nearest",
fsconfig="/i2bm/local/freesurfer/SetUpFreeSurfer.sh")
if len(gm_files) != 1:
raise ValueError("Expect one file '{0}'.".format(gm_files))
gm_file = gm_files[0]
# Get the grey matter label
gm_image = nibabel.load(gm_file)
gm_array = gm_image.get_data()
gm_array_tmp = copy.deepcopy(gm_array)
gm_array[np.where(gm_array != 3)] = 0
gm_array[np.where(gm_array == 3)] = 1
gm_array_tmp[np.where(gm_array_tmp != 42)] = 0
gm_array_tmp[np.where(gm_array_tmp == 42)] = 1
gm_array += gm_array_tmp
# Save the ventricules images
gm_image = nibabel.Nifti1Image(gm_array.astype(int),
gm_image.get_affine())
gm_file = os.path.join(outdir, "grey_matter.nii.gz")
nibabel.save(gm_image, gm_file)
# Load the affine deformation
affine = scipy.io.loadmat(mat_file)["Affine"]
affine = np.linalg.inv(affine)
if verbose > 0:
print("Affine :", affine)
return gm_file, affine
os.mkdir(convertdir)
elif args.erase:
shutil.rmtree(convertdir)
os.mkdir(convertdir)
"""
Step 1: Nifti conversions.
"""
if args.verbose > 0:
print("[info] Start Nifti conversions...")
niftifiles = {}
for modality in ["aparc+aseg", "aparc.a2009s+aseg", "aseg", "wm", "rawavg"]:
regex = os.path.join(args.subjectid, "mri", "{0}.mgz".format(modality))
niftifiles[modality] = mri_convert(
args.fsdir, regex, output_directory=None, reslice=True,
interpolation="nearest", fsconfig=args.fsconfig)
if args.verbose > 1:
print("[result] {0}: {1}.".format(modality, niftifiles[modality]))
"""
Step 2: Registration matrix.
"""
if args.verbose > 0:
print("[info] Start Registration matrix...")
regex = os.path.join(args.subjectid, "mri")
trffile = conformed_to_native_space(
args.fsdir, regex, output_directory=None, fsconfig=args.fsconfig)
if args.verbose > 1:
print("[result] trffile: {0}.".format(trffile))
if not os.path.isdir(convertdir):
os.mkdir(convertdir)
elif args.erase:
shutil.rmtree(convertdir)
os.mkdir(convertdir)
"""
Step 1: Nifti conversions.
"""
if args.verbose > 0:
print("[info] Start Nifti conversions...")
niftifiles = {}
for modality in ["aparc+aseg", "aparc.a2009s+aseg", "aseg", "wm", "rawavg"]:
regex = os.path.join(args.subjectid, "mri", "{0}.mgz".format(modality))
niftifiles[modality] = mri_convert(args.fsdir,
regex,
output_directory=None,
reslice=True,
interpolation="nearest",
fsconfig=args.fsconfig)
if args.verbose > 1:
print("[result] {0}: {1}.".format(modality, niftifiles[modality]))
"""
Step 2: Registration matrix.
"""
if args.verbose > 0:
print("[info] Start Registration matrix...")
regex = os.path.join(args.subjectid, "mri")
trffile = conformed_to_native_space(args.fsdir,
regex,
output_directory=None,
fsconfig=args.fsconfig)
if args.verbose > 1:
