You can do this in a couple of steps. First, you'll need to create a lobe annotation. You can do this in 3 ways: 1. mri_annotation2label --lobesStrict 2. mri_annotation2label --lobes 3. Custom: break up annotation and recombine: a. mri_annotation to create separate label files b. mri_mergelabels to create single label files for each lobe label c. mris_label2annot to create the lobe annotation

Next, create the WM segmentation with mri_aparc2aseg, specifying your new lobe annot and adding --labelwm. You can control the distance with --wmparc-dmax

doug

Brainiac . wrote:

Hi All,

I need to classify WM into different lobes (temporal, parietal, frontal, occipital). I tried to do the lobe mapping using parcellations from wmparc.mgz. http://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation

My problem is the "unsegmented white matter" in wmparc.mgz. My understanding is that these unsegmented areas are classified so because they are beyond 5mm from any pre-classified cortex area.

My questions: (1) So in order to classify "unsegmented WM" into lobes, do I need to take each voxel in the unsegmented WM region and then assign it to the closest cortex area to classify it into respective parcellations. Then re-group into lobes. Is this correct?

(2) Are there any tailor made function or any other easier way to do this? Is there any easier way to segment WM into lobes directly that I have missed?

Thanks, Brain

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