Example project for docker based analysis pipelines

This project can be used as a starting point for FreeSurfer based analysis pipelines. It implements a basic analysis and some scripts that execute the pipelines using docker in parallel no the available hardware.

To start download a license file from the FreeSurfer webpage. Place the license.txt file into the build-docker directory. Create the two FreeSurfer docker containers in the build-docker directory with:

cd build-docker
docker build -t fs60 -f Dockerfile .
docker build -t fs60beta -f Dockerfile_beta .

Change the search string in the runFS.sh script to point to your image series and adjust the number of cores (24) based on your machine.

Analysis pipeline

The analysis first runs a cross-sectional FreeSurfer followed by a hippocampus subfield and amygdala subfield segmentation step. The runOneFS.sh script implements these steps using the FreeSurfer docker containers (see above).

Example spreadsheet generation after cross-sectional run

In order to create a single spreadsheet with all volume, area, and thickness measures for all participants run something like this:

/bin/bash

subj="-s 00001 -s 00002"
export SUBJECTS_DIR=$(pwd)
mkdir Measures

aparcstats2table --hemi rh ${subj} --parc aparc.a2009s --report-rois True --meas area -t Measures/aparc_a2009s_rh_area.txt
aparcstats2table --hemi lh ${subj} --parc aparc.a2009s --report-rois True --meas area -t Measures/aparc_a2009s_lh_area.txt
aparcstats2table --hemi rh ${subj} --parc aparc.a2009s --report-rois True --meas volume -t Measures/aparc_a2009s_rh_volume.txt
aparcstats2table --hemi lh ${subj} --parc aparc.a2009s --report-rois True --meas volume -t Measures/aparc_a2009s_lh_volume.txt
aparcstats2table --hemi rh ${subj} --parc aparc.a2009s --report-rois True --meas thickness -t Measures/aparc_a2009s_rh_thickness.txt
aparcstats2table --hemi lh ${subj} --parc aparc.a2009s --report-rois True --meas thickness -t Measures/aparc_a2009s_lh_thickness.txt
aparcstats2table --hemi rh ${subj} --parc aparc.a2009s --report-rois True --meas foldind -t Measures/aparc_a2009s_rh_foldind.txt
aparcstats2table --hemi lh ${subj} --parc aparc.a2009s --report-rois True --meas foldind -t Measures/aparc_a2009s_lh_foldind.txt

aparcstats2table --hemi rh ${subj} --parc aparc --meas area -t Measures/aparc_desikan_rh_area.txt
aparcstats2table --hemi lh ${subj} --parc aparc --meas area -t Measures/aparc_desikan_lh_area.txt
aparcstats2table --hemi rh ${subj} --parc aparc --meas volume -t Measures/aparc_desikan_rh_volume.txt
aparcstats2table --hemi lh ${subj} --parc aparc --meas volume -t Measures/aparc_desikan_lh_volume.txt
aparcstats2table --hemi rh ${subj} --parc aparc --meas thickness -t Measures/aparc_desikan_rh_thickness.txt
aparcstats2table --hemi lh ${subj} --parc aparc --meas thickness -t Measures/aparc_desikan_lh_thickness.txt

asegstats2table ${subj} --meas volume --all-segs -t Measures/aseg_volume.txt
asegstats2table ${subj} --meas mean --all-segs -t Measures/aseg_mean_intensity.txt

Afterwards merge all the spreadsheets in Measures into a single spreadsheet using R:

> cd Measures
> R
files = Sys.glob("*.txt")
data = data.frame(src_subject_id=NA)
for (i in files) {
    print(i)
    d = read.table(i, header=TRUE, sep="\t")
    if (i == "aseg_volume.txt") {
       nn = names(d)
       for (j in seq(2,length(nn))) {
       	  nn[j] = paste(nn[j], "_vol", sep="")
       }
       names(d) = nn
    }
    if (i == "aseg_mean_intensity.txt") {
       nn = names(d)
       for (j in seq(2,length(nn))) {
       	  nn[j] = paste(nn[j], "_mean_intensity", sep="")
       }
       names(d) = nn
    }    
    data = merge(data, d, by.x=names(data)[[1]], by.y=names(d)[[1]], all.x=T, all.y=T)
}
write.csv(data,file="Measures.csv",row.names=F)

The resulting Measures.csv file will contain one row for each participant with the measures as columns.