Adding FreeSurfer functionality

bb_FS_pipeline/bb_FS_create_zip_packages.sh

+#!/usr/bin/bash
+
+#set -x
+
+mkdir -p zips
+mkdir -p logs_FS_zips
+
+for elem in `cat subj.txt ` ; do
+    if [ -d $elem/FreeSurfer ] ; then
+        if [ ! -d $elem/FreeSurfer/unusable ] ; then 
+            visit=`echo $elem | awk -F "" '{print $1}'`;
+            newName=`echo $elem | awk -F "" '{print $2$3$4$5$6$7$8}'`;
+	        echo "cd $elem ; \
+                      zip -r ../zips/${newName}_20263_${visit}_0.zip FreeSurfer -x `column_to_row $BB_BIN_DIR/bb_data/FS_files_to_exclude.txt` ; \
+                      md5sum ../zips/${newName}_20263_${visit}_0.zip > ../zips/${newName}_20263_${visit}_0.md5 ; \
+                      cd .. "; 
+        fi
+    fi
+done > jobs_zips.txt
+
+#fsl_sub -l logs_FS_zips -t jobs_zips.txt

bb_FS_pipeline/bb_FS_get_IDPs.py

+#!/bin/env python
+
+'''
+ Authors: Fidel Alfaro Almagro
+ FMRIB, Oxford University
+ 06-Apr-2019 18:03:23
+ Version $1.0
+ ProjectDir = 
+ '''
+
+import os,sys,argparse
+import bb_pipeline_tools.bb_logging_tool as LT
+
+class MyParser(argparse.ArgumentParser):
+    def error(self, message):
+        sys.stderr.write('error: %s\n' % message)
+        self.print_help()
+        sys.exit(2)
+
+class Usage(Exception):
+    def __init__(self, msg):
+        self.msg = msg
+
+
+def check_and_create_dir(dirName):
+    try:
+        os.stat(dirName)
+    except:
+        os.mkdir(dirName)
+
+def read_file(fileName):
+    result=[]
+    with open(fileName, 'r') as f:    
+        for line in f.readlines():
+            line=line.replace('\t',' ')
+            result.append([x.replace("\n",'') for x in line.split(' ')])
+    return result
+
+    
+def generate_FS_IDP_files(SUBJECTS_DIR, subject_ID, subject, dataDir, \
+                          headersDir, logger):
+
+    os.environ['SUBJECTS_DIR'] = SUBJECTS_DIR
+    statsDir = SUBJECTS_DIR + subject_ID + '/stats/'
+
+    #TODO: Include a pre-rquisite that python2.7 must be availble in the system
+    if os.path.isfile(statsDir + 'aseg.stats'):
+        LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/asegstats2table  '+\
+           ' -m volume --all-segs --tablefile ' + dataDir + 'aseg_1.txt ' +\
+           ' --subjects ' + subject_ID + ' --skip')
+        LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/asegstats2table  '+\
+            ' -m mean --all-segs --tablefile ' + dataDir + 'aseg_intensity.txt ' +\
+            ' --subjects ' + subject_ID + ' --skip')
+
+    if os.path.isfile(statsDir + 'lh.w-g.pct.stats'):
+        LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/asegstats2table ' +\
+            ' -m mean --all-segs --stats=lh.w-g.pct.stats ' +\
+            ' --tablefile ' + dataDir + 'wg_lh_mean.txt ' +\
+            ' --subjects ' + subject_ID + ' --skip')
+
+    if os.path.isfile(statsDir + 'rh.w-g.pct.stats'):
+        LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/asegstats2table ' +\
+            ' -m mean --all-segs --stats=rh.w-g.pct.stats ' +\
+            ' --tablefile ' + dataDir + 'wg_rh_mean.txt ' +\
+            ' --subjects ' + subject_ID + ' --skip')
+
+    for hemi in ["lh", "rh"]:
+        for value in ["volume", "area", "thickness"]:
+            for atlas in ["BA_exvivo", "aparc.DKTatlas", "aparc.a2009s", "aparc"]:
+                outFileName = dataDir + atlas + '_' + hemi + '_' + value + '.txt'
+                if os.path.isfile(statsDir + hemi + "." + atlas + '.stats'):
+                    LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/aparcstats2table '+\
+                        ' -m ' + value + ' --hemi=' + hemi +\
+                        ' --tablefile ' + outFileName +\
+                        ' --subjects ' + subject_ID + ' --skip -p ' + atlas )
+
+    atlas="aparc.pial"
+    value="area"
+    for hemi in ["lh", "rh"]:
+        outFileName = dataDir + atlas + '_' + hemi + '_' + value + '.txt'
+        if os.path.isfile(statsDir + hemi + '.aparc.pial.stats'):
+            LT.runCommand(logger, 'python2.7 $FREESURFER_HOME/bin/aparcstats2table '+\
+                ' -m ' + value + ' --hemi=' + hemi +\
+                ' --tablefile ' + outFileName +\
+                ' --subjects ' + subject_ID + ' --skip -p ' + atlas )
+
+    with open(os.environ["BB_BIN_DIR"]+'/bb_data/FS_initial_files.txt') as f:
+        files_generated = [x.replace('\n','').split(" ") for x in f.readlines()]
+
+    data_dict={}
+
+    for file_generated in files_generated:
+        if os.path.isfile(dataDir + file_generated[0] + '.txt'):
+            data = read_file(dataDir + file_generated[0] + '.txt')
+        else:
+            data = read_file(os.environ["BB_BIN_DIR"]+'/bb_data/FS_data_ex/' + file_generated[0] + '.txt')
+        data_dict[file_generated[0]] = data    
+
+    data_dict['ID'] = [['ID'], [subject]]
+
+    return data_dict
+
+
+#Quick consistency check
+def check_consistency(data_dict):
+
+    for file_generated in data_dict.keys():
+        if len(data_dict[file_generated])>2:
+            print("Error in " + file_generated + ': File has more than 2 lines')
+            exit(-1)
+
+        len0=len(data_dict[file_generated][0])
+        len1=len(data_dict[file_generated][1])
+
+        if len0 != len1:
+            print("Error in " + file_generated + ': Inconsistent # of features')
+            exit(-1)
+
+
+def fix_aseg_data(data_dict, subjectDir):
+
+    #Split aseg_1 into aseg_global and aseg_volume
+    data_dict['aseg_global'] = [[],[]]
+    data_dict['aseg_global'][0] = [data_dict['aseg_1'][0][0]] + data_dict['aseg_1'][0][46:]
+    data_dict['aseg_global'][1] = [data_dict['aseg_1'][1][0]] + data_dict['aseg_1'][1][46:]
+
+
+    #Variables not needed
+    vars_to_delete = ['CortexVol', 'CerebralWhiteMatterVol', \
+                      'SupraTentorialVolNotVentVox', 'MaskVol', 'SurfaceHoles']
+    ind_to_delete = []
+    for i in range(len(data_dict['aseg_global'][0])):
+        if not (data_dict['aseg_global'][0][i] in vars_to_delete):
+            ind_to_delete.append(i)
+
+    data_dict['aseg_global'][0] = [data_dict['aseg_global'][0][x] for x in ind_to_delete]
+    data_dict['aseg_global'][1] = [data_dict['aseg_global'][1][x] for x in ind_to_delete]
+
+    # For some reason, the VentricleChoroidVol is not caught by asegstats2table
+    try:
+        with open(subjectDir + '/stats/aseg.stats', 'r') as f:
+            val=[x.split(',')[3].strip() for x in f.readlines() if 'VentricleChoroidVol' in x]
+    except:
+        val=["NaN"]
+
+    data_dict['aseg_global'][0].append('VentricleChoroidVol')
+    data_dict['aseg_global'][1].append(val[0])
+
+    data_dict['aseg_volume'] = [[],[]]
+    data_dict['aseg_volume'][0] = data_dict['aseg_1'][0][0:46]
+    data_dict['aseg_volume'][1] = data_dict['aseg_1'][1][0:46]
+
+          
+    del(data_dict['aseg_1'])
+
+    #Remove the WM-hypointensities. No value in any subject
+    cols_to_remove = ['Left-WM-hypointensities', 'Right-WM-hypointensities', \
+                  'Left-non-WM-hypointensities', 'Right-non-WM-hypointensities']                  
+
+    for key in list(data_dict.keys()):
+        if key.startswith('aseg'):
+            sub_keys_to_remove = []
+            for sub_key in data_dict[key][0]:
+                for col in cols_to_remove:
+                    if col in sub_key:
+                        sub_keys_to_remove.append(sub_key)
+
+            for sub_key in sub_keys_to_remove:
+                ind = data_dict[key][0].index(sub_key)
+                del data_dict[key][0][ind]
+                del data_dict[key][1][ind]
+
+    return data_dict
+
+
+def gen_aparc_special(data_dict, subjectDir):
+
+    struct_data = []
+
+    struct_data.append(['aparc.pial_lh_area','TotalSurface','lh.aparc.pial.stats',  'PialSurfArea'])
+    struct_data.append(['aparc.pial_rh_area','TotalSurface','rh.aparc.pial.stats',  'PialSurfArea'])
+    struct_data.append(['aparc_lh_area',     'TotalSurface','lh.aparc.stats',       'WhiteSurfArea'])
+    struct_data.append(['aparc_rh_area',     'TotalSurface','rh.aparc.stats',       'WhiteSurfArea'])
+    struct_data.append(['aparc_lh_thickness',     'GlobalMeanThickness','lh.aparc.stats','MeanThickness'])
+    struct_data.append(['aparc_rh_thickness',     'GlobalMeanThickness','rh.aparc.stats','MeanThickness'])
+
+    for elem in struct_data:
+        data_dict[elem[0]][0].append(elem[1])    
+        try:
+            with open(subjectDir + '/stats/' + elem[2], 'r') as f:
+                v = [x.split(',')[3].strip() for x in f.readlines() if elem[3] in x]
+                data_dict[elem[0]][1].append(v[0])
+        except:
+            data_dict[elem[0]][1].append('NaN')
+
+    return data_dict
+
+
+def bool_FLAIR(data_dict, subjectDir):
+    if os.path.isfile(subjectDir + '/mri/FLAIR.mgz'):
+        data_dict['FLAIR'] = [['Use-T2-FLAIR-for-FreeSurfer'],['1']]
+    else:
+        data_dict['FLAIR'] = [['Use-T2-FLAIR-for-FreeSurfer'],['0']]
+
+    return data_dict
+
+
+def gen_subsegmentation(data_dict, subjectDir, subject):
+    struct_data = {}
+    struct_data['Brainstem_global'] = [['brainstemSsVolumes.v12.txt'],5]
+    struct_data['ThalamNuclei']     = [['ThalamicNuclei.v10.T1.volumes.txt'],52]
+    struct_data['AmygNuclei_lh']    = [['lh.amygNucVolumes-T1-AN.v21.txt', \
+                                        'lh.amygNucVolumes-T1.v21.txt'],10]
+    struct_data['AmygNuclei_rh']    = [['rh.amygNucVolumes-T1-AN.v21.txt', \
+                                        'rh.amygNucVolumes-T1.v21.txt'],10]
+    struct_data['HippSubfield_lh']  = [['lh.hippoSfVolumes-T1-AN.v21.txt', \
+                                        'lh.hippoSfVolumes-T1.v21.txt'],22]
+    struct_data['HippSubfield_rh']  = [['rh.hippoSfVolumes-T1-AN.v21.txt', \
+                                        'rh.hippoSfVolumes-T1.v21.txt'],22]
+
+    for struct in struct_data.keys():
+        found = False
+        data_dict[struct] = [[],[]]
+        for fil in struct_data[struct][0]:
+            if os.path.isfile(subjectDir + 'mri/' + fil):
+                with open(subjectDir + 'mri/' + fil, 'r') as f:
+                    for lin in f.readlines():
+                        lin = lin.replace('\n','').split(' ')
+                        data_dict[struct][0].append(lin[0])
+                        data_dict[struct][1].append(lin[1])
+                found = True
+                break
+               
+        if not found:
+            with open(os.environ["BB_BIN_DIR"]+'/bb_data/FS_sub_headers/' + \
+                      struct + '.txt') as f:
+                data_dict[struct][0] = [x.replace('\n','') for x in f.readlines()]
+                data_dict[struct][0] = ['NaN'] * len(data_dict[struct][0])
+        data_dict[struct][0]=['ID'] + data_dict[struct][0]
+        data_dict[struct][1]=[subject] + data_dict[struct][1]
+    return data_dict
+
+def fix_aparc_data(data_dict, subjectDir):
+
+    # Remove the column "temporalpole" in aparc files. 
+    # Unreliable measure: Very few subjects have that measure.
+    for key in list(data_dict.keys()):
+        if key.startswith('aparc'):
+            sub_keys_to_remove = []
+            for sub_key in data_dict[key][0]:
+                if 'temporalpole' in sub_key:
+                    sub_keys_to_remove.append(sub_key)
+            for sub_key in sub_keys_to_remove:
+                ind = data_dict[key][0].index(sub_key)
+
+                if ind != -1:
+                    del data_dict[key][0][ind]
+                    del data_dict[key][1][ind]
+
+
+    #Remove ETIV and BrainSegVolNotVent (They are global)
+    for key in list(data_dict.keys()):
+        if key.startswith('aparc') or key.startswith('BA_exvivo'):
+            sub_keys_to_remove = []
+            for sub_key in  data_dict[key][0]:
+                if sub_key in ['BrainSegVolNotVent' , 'eTIV']:
+                    sub_keys_to_remove.append(sub_key)
+            for sub_key in sub_keys_to_remove:
+                ind = data_dict[key][0].index(sub_key)
+                del data_dict[key][0][ind]
+                del data_dict[key][1][ind]
+
+    #Removing last colum for thickness in aparc
+    for key in list(data_dict.keys()):
+        if key.startswith('aparc') and key.endswith('thickness'):
+            sub_keys_to_remove = []
+            for sub_key in data_dict[key][0]:
+                if sub_key.endswith('MeanThickness_thickness'):
+                    sub_keys_to_remove.append(sub_key)
+            for sub_key in sub_keys_to_remove:
+                ind = data_dict[key][0].index(sub_key)
+                del data_dict[key][0][ind]
+                del data_dict[key][1][ind]
+
+    #Removing the last column for areas, also in BA
+    for key in list(data_dict.keys()):
+        if key.endswith('area'):
+            sub_keys_to_remove = []
+            for sub_key in data_dict[key][0]:
+                if sub_key.endswith('WhiteSurfArea_area'):
+                    sub_keys_to_remove.append(sub_key)
+            for sub_key in sub_keys_to_remove:
+                ind = data_dict[key][0].index(sub_key)
+                del data_dict[key][0][ind]
+                del data_dict[key][1][ind]
+
+
+    return data_dict
+
+#Remove first feature in case it is the subject ID (except for ID itself)
+def remove_first_feature(data_dict, subject):
+    for key in list(data_dict.keys()):
+        if key != "ID":
+            if (data_dict[key][1][0] == subject) or  \
+               (data_dict[key][1][0] == ('FS_' + subject)) or \
+               (data_dict[key][1][0] == ''):
+                del data_dict[key][0][0]
+                del data_dict[key][1][0]
+    return data_dict
+
+def fix_headers(data_dict):
+
+    #Applying some general replacing rules for the categories
+    replace_rules = [['.', '-'], \
+                     ['BA_exvivo', 'BA-exvivo'],\
+                     ['AmygNuclei_lh', 'AmygNuclei_lh_volume'],\
+                     ['AmygNuclei_rh', 'AmygNuclei_rh_volume'],\
+                     ['Brainstem_global', 'Brainstem_global_volume'],\
+                     ['HippSubfield_lh', 'HippSubfield_lh_volume'],\
+                     ['HippSubfield_rh', 'HippSubfield_rh_volume'],\
+                     ['wg_lh_mean','wg_lh_intensity-contrast'],\
+                     ['wg_rh_mean','wg_rh_intensity-contrast'],\
+                     ['aparc_lh', 'aparc-Desikan_lh'],\
+                     ['aparc_rh', 'aparc-Desikan_rh'],\
+                     ['FLAIR','Use-T2-FLAIR-for-FreeSurfer']]
+    
+    for key in list(data_dict.keys()):
+        new_key=key
+        for rule in replace_rules:
+            if rule[0] in new_key:
+                new_key = new_key.replace(rule[0],rule[1])                
+                data_dict[new_key] = data_dict.pop(key)
+
+    #Renaming some special cases
+    structs = [['aseg_global', 'lhSurfaceHoles', 'aseg_lh_number', 'HolesBeforeFixing'],\
+               ['aseg_global', 'rhSurfaceHoles', 'aseg_rh_number', 'HolesBeforeFixing'],\
+               ['aseg_global', 'BrainSegVol-to-eTIV', 'aseg_global_volume-ratio', 'BrainSegVol-to-eTIV'],\
+               ['aseg_global', 'MaskVol-to-eTIV', 'aseg_global_volume-ratio', 'MaskVol-to-eTIV']]
+
+    for struct in structs:
+        index = data_dict[struct[0]][0].index(struct[1])
+        if struct[2] not in data_dict.keys():
+            data_dict[struct[2]] = [struct[3]],[data_dict[struct[0]][1][index]]
+        else:
+            data_dict[struct[2]][0].append(struct[3])
+            data_dict[struct[2]][1].append(data_dict[struct[0]][1][index])
+        del data_dict[struct[0]][0][index]
+        del data_dict[struct[0]][1][index]        
+
+
+
+    for metric in ['volume', 'intensity']:
+        old_key = 'aseg_' + metric
+        for i in range(len(data_dict[old_key][0])):
+            if 'Left-' in data_dict[old_key][0][i]: 
+                new_name = data_dict[old_key][0][i].replace('Left-','')
+                new_key = 'aseg_lh_' + metric
+                
+                if new_key not in data_dict.keys():
+                    data_dict[new_key] = [[],[]]
+                data_dict[new_key][0].append(new_name)
+                data_dict[new_key][1].append(data_dict[old_key][1][i])
+            elif 'Right-' in data_dict[old_key][0][i]: 
+                new_name = data_dict[old_key][0][i].replace('Right-','')
+                new_key = 'aseg_rh_' + metric
+                
+                if new_key not in data_dict.keys():
+                    data_dict[new_key] = [[],[]]
+                data_dict[new_key][0].append(new_name)
+                data_dict[new_key][1].append(data_dict[old_key][1][i])
+            else:
+                new_name = data_dict[old_key][0][i]
+                new_key = 'aseg_global_' + metric
+                if new_key not in data_dict.keys():
+                    data_dict[new_key] = [[],[]]
+                data_dict[new_key][0].append(new_name)
+                data_dict[new_key][1].append(data_dict[old_key][1][i])
+
+        del(data_dict[old_key])
+
+    for i in range(len(data_dict['aseg_global'][0])):
+        if data_dict['aseg_global'][0][i].startswith('lh'):
+            new_name = data_dict['aseg_global'][0][i].replace('lh','').replace('Vol','')
+            data_dict['aseg_lh_volume'][0].append(new_name)
+            data_dict['aseg_lh_volume'][1].append(data_dict['aseg_global'][1][i])
+        elif data_dict['aseg_global'][0][i].startswith('rh'):
+            new_name = data_dict['aseg_global'][0][i].replace('rh','').replace('Vol','')
+            data_dict['aseg_rh_volume'][0].append(new_name)
+            data_dict['aseg_rh_volume'][1].append(data_dict['aseg_global'][1][i])
+        else:
+            new_name = data_dict['aseg_global'][0][i].replace('Vol','')
+            data_dict['aseg_global_volume'][0].append(new_name)
+            data_dict['aseg_global_volume'][1].append(data_dict['aseg_global'][1][i])
+
+    del(data_dict['aseg_global'])  
+
+    # Split ThalamNuclei into Left and Right
+    data_dict['ThalamNuclei_lh_volume'] = [[],[]]
+    data_dict['ThalamNuclei_rh_volume'] = [[],[]]
+    for i in range(len(data_dict['ThalamNuclei'][0])):
+        if "Left" in data_dict['ThalamNuclei'][0][i]:
+            new_name = data_dict['ThalamNuclei'][0][i].replace('Left-','')
+            data_dict['ThalamNuclei_lh_volume'][0].append(new_name)
+            data_dict['ThalamNuclei_lh_volume'][1].append(data_dict['ThalamNuclei'][1][i])
+
+        elif "Right" in data_dict['ThalamNuclei'][0][i]:
+            new_name = data_dict['ThalamNuclei'][0][i].replace('Right-','')
+            data_dict['ThalamNuclei_rh_volume'][0].append(new_name)
+            data_dict['ThalamNuclei_rh_volume'][1].append(data_dict['ThalamNuclei'][1][i])
+    del(data_dict['ThalamNuclei'])            
+
+    #Removing redundant prefix and sufix in BA_excvivo
+    BAs = ['_exvivo_area','_exvivo_thickness', '_exvivo_volume']
+    BA_keys = [key for key in list(data_dict.keys()) if key.startswith('BA-exvivo')]
+    for key in BA_keys:
+        for i in range(len(data_dict[key][0])):
+            for BA in BAs:
+                data_dict[key][0][i] = data_dict[key][0][i].replace(BA,'').replace('rh_','').replace('lh_','')
+
+    #Removing redundant prefix and sufix in aparc
+    aparcs = ['_area','_thickness', '_volume','-area','-thickness', '-volume']
+    aparc_keys = [key for key in list(data_dict.keys()) if key.startswith('aparc')]
+    for key in aparc_keys:
+        for i in range(len(data_dict[key][0])):
+            for aparc in aparcs:
+                data_dict[key][0][i] = data_dict[key][0][i].replace(aparc,'').replace('rh_','').replace('lh_','')
+
+    #Changing weird and inconsistent characters
+    for key in list(data_dict.keys()):
+        for i in range(len(data_dict[key][0])):
+            data_dict[key][0][i] = data_dict[key][0][i].replace('_','-').replace('&','+')
+
+    return data_dict
+
+def save_data(data_dict, SUBJECTS_DIR):
+
+    with open(os.environ["BB_BIN_DIR"]+'/bb_data/FS_headers.txt') as f:
+        final_headers = [x.replace('\n','') for x in f.readlines()]
+
+    temp_headers={}
+
+    for key in list(data_dict.keys()):
+        if key in ['ID', 'Use-T2-FLAIR-for-FreeSurfer']:
+            temp_headers[key] = data_dict[key][1][0]
+        else: 
+            for i in range(len(data_dict[key][0])):
+                temp_headers[key+"_"+data_dict[key][0][i]] = data_dict[key][1][i]
+
+    for x in final_headers:
+        if x not in temp_headers.keys():
+            temp_headers[x] = "NaN"
+
+    with open(SUBJECTS_DIR + '/IDP_files/FS_IDPs.txt','w') as f:
+        values = [temp_headers[x] for x in final_headers]
+        values_str = " ".join(values)
+        f.write("%s\n" % values_str)
+        f.close()
+
+
+def save_headers_info(data_dict, SUBJECTS_DIR):
+
+    with open(os.environ["BB_BIN_DIR"]+'/bb_data/FS_final_headers.txt') as f:
+        final_headers = [x.replace('\n','') for x in f.readlines()]
+
+    temp_headers={}
+
+    for key in list(data_dict.keys()):
+        if key in ['ID', 'Use-T2-FLAIR-for-FreeSurfer']:
+            temp_headers[key] = data_dict[key][1][0]
+        else: 
+            for i in range(len(data_dict[key][0])):
+                temp_headers[key+"_"+data_dict[key][0][i]] = data_dict[key][1][i]
+
+    for x in final_headers:
+        if x not in temp_headers.keys():
+            temp_headers[x] = "NaN"
+
+    with open(SUBJECTS_DIR + '/IDP_files/FS_headers_info.txt','w') as f:
+        values = [temp_headers[x] for x in final_headers]
+        values_str = " ".join(values)
+        f.write("%s\n" % values_str)
+
+        f.close()
+
+
+def bb_FS_get_IDPs(subject):
+
+    logger  = LT.initLogging(__file__, subject)
+    #    logger  = LT.initLogging('log', subject)
+    logDir  = logger.logDir
+    baseDir = logDir[0:logDir.rfind('/logs/')]
+
+    SUBJECTS_DIR = os.getcwd() + '/' + subject + '/'
+    subject_ID   = 'FS_' + subject
+
+    subjectDir   = SUBJECTS_DIR + subject_ID + '/'
+
+    if not os.path.isdir(subjectDir):
+        subject_ID = 'FreeSurfer'
+        subjectDir   = SUBJECTS_DIR + subject_ID + '/'
+        if not os.path.isdir(subjectDir):
+            print("Error: FreeSurfer has not been run on this subject")
+            exit(-1)
+
+    dataDir      = SUBJECTS_DIR + subject_ID + '/data/'
+    headersDir   = SUBJECTS_DIR + subject_ID + '/headers/'
+
+    check_and_create_dir(dataDir)
+    check_and_create_dir(headersDir)
+
+    data_dict = generate_FS_IDP_files(SUBJECTS_DIR, subject_ID, subject, \
+                                       dataDir, headersDir, logger)
+    data_dict = fix_aseg_data(data_dict, subjectDir)
+    data_dict = gen_aparc_special(data_dict, subjectDir)
+    data_dict = gen_subsegmentation(data_dict, subjectDir, subject)
+    data_dict = bool_FLAIR(data_dict, subjectDir)
+    data_dict = fix_aparc_data(data_dict,subjectDir)    
+    data_dict = remove_first_feature(data_dict, subject)
+    data_dict = fix_headers(data_dict)    
+
+    check_consistency(data_dict)   
+    save_data(data_dict, SUBJECTS_DIR)
+
+    LT.finishLogging(logger)
+
+def main(): 
+  
+    parser = MyParser(description='BioBank FreeSurfer IDP generation Tool')
+    parser.add_argument("subjectFolder", help='Subject Folder')
+
+    argsa = parser.parse_args()
+
+    subject = argsa.subjectFolder
+    subject = subject.strip()
+
+    if subject[-1] =='/':
+        subject = subject[0:len(subject)-1]
+    
+    if not os.path.isdir(subject):
+        print('Error: The subject ' + subject + ' does not exist')
+        exit(-1)
+
+    job1 = bb_FS_get_IDPs(subject)
+             
+if __name__ == "__main__":
+    main()

bb_FS_pipeline/bb_FS_run.sh

+#!/bin/bash
+
+. $BB_BIN_DIR/bb_pipeline_tools/bb_set_header 
+
+if [ ! -f $1/T1/T1_unbiased.nii.gz ] ; then 
+
+    echo "There is no T1/T1_unbiased.nii.gz -- FreeSurfer cannot run"
+    exit -1
+
+else
+
+    if [ "$2" == "" ] ; then