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January 21, 2019 15:42
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Collecting Freesurfer6 features from XNAT
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import json | |
import pandas as pd | |
import pyxnat | |
c = pyxnat.Interface(config='/home/grg/.xnat_bsc.cfg') | |
# Collect experiments | |
experiments = json.load(open('/home/grg/Downloads/mri_list.json')) | |
# Querying FreeSurfer resource -if any- from each experiment | |
tables = [[], [], []] | |
for e in experiments: | |
s = c.array.experiments(experiment_id=e, columns=['subject_label']).data[0]['subject_label'] | |
r = c.select.experiment(e).resource('FREESURFER6') | |
if not r.exists(): continue | |
volumes = [r.hippoSfVolumes(), r.aseg(), r.aparc()] | |
for each, table in zip(volumes, tables): | |
each['subject'] = s | |
table.append(each) | |
# Convert to dataframes | |
hippoSfVolumes = pd.concat(tables[0]).set_index('subject').sort_index() | |
aseg = pd.concat(tables[1]).set_index('subject').sort_index() | |
aparc = pd.concat(tables[2]).set_index('subject').sort_index() | |
# Creating pivot tables | |
aparc.to_excel('/tmp/aparc_JH.xlsx') | |
import pandas as pd | |
t = pd.read_excel('/tmp/aparc_JH.xlsx').set_index('subject') | |
pd.pivot_table(t, | |
values='value', | |
columns='region', | |
index=t.index).head() |
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