Cortical Thickness
Contents
Page describing how we analyze cortical thickness with freesurfer
Step 1: In a terminal, convert the PAR/REC files to nifti images. You may not need to do this if you have already gone through the Anatomy_Pipeline
cd /home/projects/MRI/[subid] parrec2nii -c -b *.PAR
Step 2: In MATLAB compute the root mean squared (RMS) image and then ac-pc align. If a subject has multiple images then the rms operation should be run on each image and then a cell-array with paths to all the images can be pushed through mrAnatAverageAcpcNifti resulting in a very nice anatomy
T1path = 'Path to t1 weighted image';
T1path = mri_rms(T1path); % Root mean squared image
im = niftiRead(T1path); % Read root mean squared image
voxres = diag(im.qto_xyz)'; % Get the voxel resolution of the image (mm)
mrAnatAverageAcpcNifti({T1path}, '/home/projects/anatomy/[subid]/t1_acpc.nii.gz', [], voxres(1:3))
Freesurfer Segmentation
Freesurfer is a useful tool for segmenting a T1-weighted image and building a cortical mesh. To segment the subject's T1-weighted image using freesurfer from the command line type:
recon-all -i /home/projects/anatomy/[subid]/t1_acpc_.nii.gz -subjid [subid] -all
Or even better use this handy matlab function written by Jon Winawer to run freesurfer and then also build some useful files that we like to use for data visualization such as a high resolution gray/white segmentation.
fs_autosegmentToITK([subid], '/home/projects/anatomy/[subid]/t1_acpc.nii.gz')
