aal_roi.sh

#!/bin/bash

# This script aligns the MNI brain to functional image space then uses this transform to register the AAL atlas to the funcitonal image. Masks are created from the atlas and the functional image is masked. The output files can be found in $caseDir/images_masked and $caseDir/masks.

topDir=$1
dataPath=$2
dataFile=$(basename $dataPath)

# extract filename from data
filename=${dataFile%.nii*}

for caseDir in $(ls -d $topDir/*CVRTRT8P*); do
  
	# transformation from MNI to functional space
	flirt -in "$caseDir/output/mean_baselineCBF.nii" -ref /usr/local/fsl/data/standard/MNI152_T1_2mm_brain -omat "$caseDir/temp/func2MNI.mat" -dof 12 -interp trilinear
	convert_xfm -omat "$caseDir/temp/MNI2func.mat" -inverse "$caseDir/temp/func2MNI.mat"
	flirt -in aal_MNI_V4.nii -ref "$caseDir/output/mean_baselineCBF.nii" -applyxfm -init "$caseDir/temp/MNI2func.mat" -out "$caseDir/temp/aal_func.nii" -dof 12 -interp nearestneighbour


	# make subdirectories to store ROI data
	if [ ! -e $caseDir/masks ]; then mkdir $caseDir/masks; fi
	#if [ ! -e $caseDir/images_masked ]; then mkdir $caseDir/images_masked; fi
	if [ ! -e $caseDir/output/mean_baselineCBF_images_masked ]; then mkdir $caseDir/output/mean_baselineCBF_images_masked; fi

	# create a mask for each ROI
	IFS=$'\n'
	for line in $(tail -n +2 aal_MNI_V4.txt); do
	
		i=$(echo $line | awk '{print $1}')
		label=$(echo $line | awk '{print $2}')
			
		fslmaths $caseDir/temp/aal_func.nii.gz -thr $i -uthr $i -bin $caseDir/masks/${label}_func

		fslmaths $caseDir/$dataPath -mas $caseDir/masks/${label}_func.nii.gz $caseDir/output/mean_baselineCBF_images_masked/${filename}_${label}

	done	
	

done