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Mapping automatic segmentations to the functional space

1.0 Mapping the segmentations

The cortical and subcortical segmentations automatically generated by freesurfer can be mapped into the functional space, which can be useful for doing region of interest (ROI) analysis. There are two commands to perform this: aseg2feat (subcortical) and aparc2feat (cortical). Information about them can be obtained by running them with --help. To run them on the bert functional data, run: 

aseg2feat --feat fbert.feat

and 

aparc2feat --feat fbert.feat

The these commands will create three files in fbert.feat/reg/freesurfer: aseg.img, lh.aparc.img, and rh.aparc.img. These are segmentations, meaning that each voxel has an integer value that corresponds to a particular structure. The mapping from structure number to name for aseg (subcortical) is given in ${FREESURFER_HOME}/tkmeditColorsCMA. For aparc (cortical), it can be found in ${FREESURFER_HOME}/Simple_surface_labels2002.txt.

2.0 Creating binary masks

The segmentation for a particular structure can be extracted to create a binary mask (i.e., a volume where the voxel value is 1 if it is in the structure and 0 otherwise). To make a binary mask of the left putamen, which has been assigned label 12 (see ${FREESURFER_HOME}/tkmeditColorsCMA), use the following command: 

avwmaths ./fbert.feat/reg/freesurfer/aseg.img \
    -thr 12 -uthr 12 \
    ./fbert.feat/reg/freesurfer/lh.putamen.img

To view this binary mask on the anatomical: 

tkmedit bert orig -aux brain \
    -overlay ./fbert.feat/reg/freesurfer/lh.putamen.img \
    -overlay-reg ./fbert.feat/reg/freesurfer/anat2exf.register.dat \
    -fthresh 0.5 -fmid 1 -fslope 1 \
    -segmentation ${SUBJECTS_DIR}/bert/mri/aseg \
    ${FREESURFER_HOME}/tkmeditColorsCMA

You should see the image below:BR attachment:tkm-lh.putamen-cor-128-small.jpg