Summary of what happened:
I’m new to fmriprep, and have been trying to use it to process my T1 data.
I used MNI152NLin2009cAsym as the template with a shape of 193x229x193. However, I found some of my output normalized images have a shape different from this.
Command used (and if a helper script was used, a link to the helper script or the command generated):
data = getPandas('pat_data')
conf = getConfig('data')
train_inds = conf['indices']['pat']['train']
test_inds = conf['indices']['pat']['test']
data = data.loc[train_inds + test_inds].reset_index(drop=True)
keys = data['KEY'].values
for i, key in enumerate(keys):
print('Processing {}'.format(key))
cmd = 'fmriprep-docker data/bids/pat_raw data/bids/pat_fmriprep -i nipreps/fmriprep:latest --mem 8192 --output-space MNI152NLin2009cAsym --fs-no-reconall --anat-only --skip_bids_validation'
cmd += ' --participant-label {}'.format(key)
if not os.path.exists(os.path.join('data', 'bids', 'pat_fmriprep', 'sub-{}'.format(key))):
os.system(cmd)
Version:
Environment (Docker, Singularity, custom installation):
Docker