• FsTutorial
• Diffusion
• DTIscripts

Be sure to source FreeSurfer before trying to run any of the following scripts.

subjects.csh

Use this script to set the 'SUBJECTS_DIR' and 'TUTORIAL_DIR' parameters, as well as assigning variouos subject data sub-sets (normal subjects, lesioned subjects, both groups). The 'TUTORIAL_DATA' represents the file path of where the tutorial data is being stored.

{{{#!/bin/tcsh -ef

setenv SUBJECTS_DIR $TUTORIAL_DATA/diffusion_recons setenv TUTORIAL_DIR $TUTORIAL_DATA/diffusion_tutorial

set SUBJECTS = (Diff001 Diff002 Diff003 Diff004 Diff005 Diff006 Diff007 Diff008 Diff009 Diff010) set LESION_SUBJECTS = (LDiff006 LDiff007 LDiff008 LDiff009 LDiff010) set SUBJECTS_AND_LESION_SUBJECTS = (Diff001 Diff002 Diff003 Diff004 Diff005 LDiff006 LDiff007 LDiff008 LDiff009 LDiff010) }}}

DiffPreproc.csh

{{{#!/bin/tcsh –ef

• #

source subjects.csh

# Run dt_recon on all subjects foreach subj ($SUBJECTS)

• echo $subj set outdir = $TUTORIAL_DIR/$subj/dtrecon mkdir -p $outdir set dicomfile = $TUTORIAL_DIR/$subj/orig/*-1.dcm set cmd = (dt_recon --i $dicomfile --s $subj --o $outdir) echo $cmd eval $cmd

end }}} Output: dwi.nii, dwi.mghdti.bvecs, dwi.mghdti.bvals, dwi-ec.nii, lowb.nii, bvecs.dat, bvals.dat, eigvec[123].nii, eigvals.nii, tensor.nii, dwirvar.nii, ivc.nii, adc.nii, radialdiff.nii, vr.nii, ra.nii, fa.nii, fa-tal.nii, register.dat.

AlignAnat2Diff.csh

{{{#!/bin/tcsh -ef

• #

source subjects.csh

# Loop through each subject foreach subj ($SUBJECTS)

• echo $subj set outdir = $TUTORIAL_DIR/$subj/dtrecon # For each subject's wmparc and aparc+aseg volumes resample them to diffusion space foreach vol (wmparc aparc+aseg)
  • set vol = $SUBJECTS_DIR/$subj/mri/$vol.mgz set vol2diff = ${vol:r}2diff.mgz set cmd = (mri_vol2vol --mov $outdir/lowb.nii --targ $vol --inv --interp nearest \
    • --o $vol2diff --reg $outdir/register.dat --no-save-reg)
    echo $cmd eval $cmd
  end

end }}} Output: wmparc2diff.mgz, aparc+aseg2diff.mgz.

DiffMasking.csh

{{{#!/bin/tcsh -ef

• #

source subjects.csh

# Loop through each subject foreach subj ($SUBJECTS)

• echo $subj set outdir = $TUTORIAL_DIR/$subj/dtrecon # Use wmparc2diff.mgz to mask out noise in the fa.nii, adc.nii, and ivc.nii volumes foreach vol (fa adc ivc)
  • set cmd = (mri_mask $outdir/$vol.nii $SUBJECTS_DIR/$subj/mri/wmparc2diff.mgz \
    • $outdir/${vol}-masked.mgz)
    echo $cmd eval $cmd
  end

end }}} Output: fa-masked.mgz, adc-masked.mgz, ivc-masked.mgz.

AlignAnatCVSToAvg.csh

{{{#!/bin/tcsh -ef

• #

source subjects.csh

set interp = trilin set template = $SUBJECTS_DIR/cvs_avg35/mri/norm.mgz

# Loop through each subject foreach subj ($SUBJECTS)

• echo $subj set outdir = $TUTORIAL_DIR/$subj/dtrecon set morph = $SUBJECTS_DIR/$subj/cvs/fullCVSmorph-to-avg35template.m3z

# Resample the fa-masked.mgz, adc-masked.mgz, and ivc-masked.mgz to common CVS space

• foreach vol (fa adc ivc)
  • set vol = $outdir/${vol}-masked.mgz echo $vol set outvol = ${vol:r}.ANAT+CVS-to-avg35.mgz echo $outvol set cmd = (mri_vol2vol --targ $template --m3z $morph --noDefM3zPath \
    • --reg $outdir/register.dat --mov $vol \ --o $outvol --interp $interp --no-save-reg)
    echo $cmd eval $cmd
  end

end }}} Output: fa-masked.ANAT+CVS-to-avg35.v2v.mgz, adc-masked.ANAT+CVS-to-avg35.v2v.mgz, ivc-masked.ANAT+CVS-to-avg35.v2v.mgz.

GroupAnalysis.csh

{{{#!/bin/tcsh -ef

source subjects.csh

set outdir = $TUTORIAL_DIR/GLM mkdir -p $outdir

# Assemble input for group analysis set type = CVS-to-avg35 # alternatively could be 'TAL' or 'MNI' set prefix = fa-masked # alternatively could be adc-masked or ivc-masked set inputfiles = ()

foreach subj ($SUBJECTS)

• set inputfiles=($inputfiles $TUTORIAL_DIR/$subj/dtrecon/${prefix}.ANAT+${type}.mgz)

end

set cmd = (mri_concat --i $inputfiles --o $outdir/GroupAnalysis.${prefix}.${type}.Input.mgz) echo $cmd eval $cmd

# Create average of the input images for visualization set cmd = (mri_average $inputfiles $outdir/Average.{$prefix}.${type}.Input.mgz) echo $cmd eval $cmd

set cmd = (mri_glmfit --y $outdir/GroupAnalysis.{$prefix}.${type}.Input.mgz \

• --fsgd group_analysis.fsgd dods --C contrast.mtx \ --glmdir $outdir/gender_age.{$prefix}.${type}.glmdir --mgz)

echo $cmd eval $cmd }}} Output: gender_age.fa-masked.CVS-to-avg35.glmdir, dof.dat, mri_glmfit.log, y.fsgd, X.mat, contrast/Xg.dat, contrast/rstd.mgz, contrast/rvar.mgz, contrast/beta.mgz, contrast/fwhm.dat, contrast/sar1.mgz, contrast/mask.mgz.