Dear FreeSurfer Developers,
Currently we are trying to analyze our functional data (optical imaging) using ROI’s that are defined on the basis of FreeSurfer Segmentation. In order to do this, we need a 3 dimensional mask in which a particular region as identified by FreeSurfer is used as a mask for analyzing our functional data. How can we output from FreeSurfer what each voxel is classified as (hippocampus, etc.), or a mask having a value of 1 for each region, and a 0 for every other voxel. Also, what coordinate space would this be in? We would prefer either MNI or TAI (or a way to get into either space).
Thanks you so much for your help.
Sincerely,
Mark Fletcher
CNL Lab UIUC
Hi Mark
why go to a standard space? It's probably easier to stay in the subject coordinate system. The aparc+aseg.mgz contains all the cortical and subcortical labels you want, defined in $FREESURFER_HOME/FreeSurferColotLUT.txt. You can extract individual labels to create binary masks either using mri_binarize --match or mri_extract_label. You'll need to map them into functional coordinates with mri_vol2vol after creating a registration between them (usually with bbregister).
cheers Bruce
On Wed, 8 Aug 2012, Mark Fletcher wrote:
Dear FreeSurfer Developers,
Currently we are trying to analyze our functional data (optical imaging) using ROI?s that are defined on the basis of FreeSurfer Segmentation. In order to do this, we need a 3 dimensional mask in which a particular region as identified by FreeSurfer is used as a mask for analyzing our functional data. How can we output from FreeSurfer what each voxel is classified as (hippocampus, etc.), or a mask having a value of 1 for each region, and a 0 for every other voxel. Also, what coordinate space would this be in? We would prefer either MNI or TAI (or a way to get into either space).
Thanks you so much for your help.
Sincerely,
Mark Fletcher
CNL Lab UIUC
freesurfer@nmr.mgh.harvard.edu