Mri binarize: Difference between revisions
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If you have data from different time points, as with the booth data, and want to make comparisons of ROI's across time points you'll want to be looking at the same voxels. Here seems to be the way to do that freesurfer. | If you have data from different time points, as with the booth data, and want to make comparisons of ROI's across time points you'll want to be looking at the same voxels. Here seems to be the way to do that freesurfer. | ||
At this point you should have conducted group stats ( | At this point you should have conducted group stats (mri_glmfit) and pulled out whatever ROI's of interest. Now you'll convert your group average .annot label file | ||
to a volume, so that we can use the binarize function. | to a volume, so that we can use the binarize function. | ||
Revision as of 15:25, 29 March 2017
If you have data from different time points, as with the booth data, and want to make comparisons of ROI's across time points you'll want to be looking at the same voxels. Here seems to be the way to do that freesurfer.
At this point you should have conducted group stats (mri_glmfit) and pulled out whatever ROI's of interest. Now you'll convert your group average .annot label file to a volume, so that we can use the binarize function.
For T1 & T2
mri_label2vol --annot T1_rh.200functional_subclusters.annot --temp f.nii --o rh.T1_200funclust.mgz --subject fsaverage --hemi rh --reg reg.2mm.mni152.dat mri_label2vol --annot T1_lh.200functional_subclusters.annot --temp f.nii --o lh.T1_200funclust.mgz --subject fsaverage --hemi lh --reg reg.2mm.mni152.dat mri_label2vol --annot T2_rh.200functional_subclusters.annot --temp f.nii --o rh.T2_200funclust.mgz --subject fsaverage --hemi rh --reg reg.2mm.mni152.dat mri_label2vol --annot T2_lh.200functional_subclusters.annot --temp f.nii --o lh.T2_200funclust.mgz --subject fsaverage --hemi lh --reg reg.2mm.mni152.dat
Now that you have volumes, that mri_binarize function will produce 3 volumes with significant voxels set to 1 (or whatever value specified). One with sig. voxels in A but not B, one with sig. voxels in B but not A, and one with overlapping sig. voxels in both A and B.
For Left and Right Hemi
mri_binarize mri_binarize
Then we convert our new volumes back to label files.
mri_cor2label mri_cor2label
And, finally apply the new annot file to each subject
For Left and Right Hemi
mri_surf2surf