subjects = pd.read_csv('/scr/ilz3/myelinconnect/subjects.csv') subjects=list(subjects['DB']) subjects.remove('KSMT') labels= [11, 12, 13, 16, 18] + range(30,42) templates={'seg': '/scr/ilz3/myelinconnect/struct/seg/{subject}*seg_merged.nii.gz'} mask_file = '/scr/ilz3/myelinconnect/struct/myelinated_thickness/subcortex_mask/%s_subcortical_mask.nii.gz' for subject in subjects: select = SelectFiles(templates) select.inputs.subject = subject select.run() seg_file = select.aggregate_outputs().seg binarize = Binarize(match = labels, out_type = 'nii.gz') binarize.inputs.binary_file = mask_file%subject binarize.inputs.in_file=seg_file binarize.run()