def smooth_data_as_texture(data, subject, hemi):
"""To smooth the data, save them as texture,
surfs2surf and extract the data """
from nibabel.gifti import read, write, GiftiImage, GiftiDataArray as gda
file_raw = '/tmp/data.gii'
file_smooth = '/tmp/smooth_data.gii'
write(GiftiImage(darrays=[gda(data=data.astype('float32'))]), file_raw)
os.system('$FREESURFER_HOME/bin/mri_surf2surf' +
' --srcsubject %s' % subject + ' --srcsurfval %s' % file_raw +
' --trgsurfval %s' % file_smooth + ' --trgsubject %s' % subject +
' --hemi %s' % hemi + ' --nsmooth-out 2')
return read(file_smooth).darrays[0].data
def project_volume(work_dir, subject, do_bbr=True):
# first find the session where T1w and T2w files could be
ref_file = sorted(
glob.glob(
os.path.join(work_dir, subject, 'ses-*', 'anat',
'*-highres_T1w.nii*')))[-1]
# session = ref_file.split('/')[-3]
anat_dir = os.path.dirname(ref_file)
write_dir = os.path.join(anat_dir, 'analysis')
if not os.path.exists(write_dir):
os.mkdir(write_dir)
os.environ['SUBJECTS_DIR'] = anat_dir
data = {}
for modality in ['T1w', 'T2w']:
if modality == ['T1w']:
image = ref_file
else:
image = sorted(
glob.glob(
os.path.join(work_dir, subject, 'ses-*', 'anat',
'*-highres_T2w.nii*')))[-1]
image_ = closing(image)
# --------------------------------------------------------------------
# run the projection using freesurfer
print("image", image)
basename = os.path.basename(image).split('.')[0]
if modality == 'T1w':
bbreg = BBRegister(subject_id=subject,
source_file=image,
init='header',
contrast_type='t1')
else:
# use BBR registration to finesse the coregistration
bbreg = BBRegister(subject_id=subject,
source_file=image,
init='header',
contrast_type='t2')
regheader = os.path.join(anat_dir,
basename + '_bbreg_%s.dat' % subject)
bbreg.run()
if 1:
# output names
# the .gii files will be put in the same directory as the input
left_tex = os.path.join(write_dir, basename + '_lh.gii')
right_tex = os.path.join(write_dir, basename + '_rh.gii')
# run freesrufer command for projection
os.system(
'$FREESURFER_HOME/bin/mri_vol2surf --src %s --o %s '
'--out_type gii --srcreg %s --hemi lh --projfrac-avg 0 1 0.1' %
(image_, left_tex, regheader))
os.system(
'$FREESURFER_HOME/bin/mri_vol2surf --src %s --o %s '
'--out_type gii --srcreg %s --hemi rh --projfrac-avg 0 1 0.1' %
(image_, right_tex, regheader))
# resample to fsaverage
left_smooth_tex = os.path.join(write_dir,
basename + '_fsaverage_lh.gii')
right_smooth_tex = os.path.join(write_dir,
basename + '_fsaverage_rh.gii')
os.system('$FREESURFER_HOME/bin/mri_surf2surf --srcsubject %s '
'--srcsurfval %s --trgsurfval %s --trgsubject ico '
'--trgicoorder 7 --hemi lh' %
(subject, left_tex, left_smooth_tex))
os.system('$FREESURFER_HOME/bin/mri_surf2surf --srcsubject %s '
'--srcsurfval %s --trgsubject ico --trgicoorder 7 '
'--trgsurfval %s --hemi rh' %
(subject, right_tex, right_smooth_tex))
data[modality] = {
'lh': nib.load(left_smooth_tex).darrays[0].data,
'rh': nib.load(right_smooth_tex).darrays[0].data
}
else:
from surfer import project_volume_data
data[modality] = {}
for hemi in ['lh', 'rh']:
data_ = project_volume_data(image_,
hemi,
regheader,
projarg=[0, 1., .1],
smooth_fwhm=0)
data[modality][hemi] = data_
# reset subject_dir to set fsaverage
os.environ['SUBJECTS_DIR'] = os.path.join(work_dir, subject, 'ses-00',
'anat')
for hemi in ['lh', 'rh']:
ratio = data['T1w'][hemi] / data['T2w'][hemi]
from nibabel.gifti import write, GiftiImage, GiftiDataArray as gda
file_ratio = os.path.join(write_dir, 't1_t2_ratio_%s.gii' % hemi)
write(GiftiImage(darrays=[gda(data=ratio.astype('float32'))]),
file_ratio)
"""