Hi Nicolas

I’m not sure what is going wrong as your basic procedure looks correct. I would start by building a gcs from a single subject, then labeling that same subject and seeing if you recover the manual label (more-or-less)

Cheers

Bruce

From: freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> On Behalf Of Henzen Nicolas
Sent: Wednesday, July 27, 2022 2:24 AM
To: 'freesurfer@nmr.mgh.harvard.edu' <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] Help with improving the training of an alternative atlas for medial temporal lobe subregions

        External Email - Use Caution        

Hi all,

We are aiming at training an alternative atlas of some subregions in the medial temporal lobe using FreeSurfer.

As training examples, we manually segmented the subregions using tkmedit and tksurf. In this process we deleted the original segmentation labels around our new regions of interest (see Figure 1). Then, we trained the atlas and parcellated new data as follows:

# Train atlases

for hemi in lh rh; do

mris_ca_train -n 2 \

    -t ./doc/LUT.txt \

    ${hemi} \

    sphere.reg \

    CUSTOM_ROIs.annot \

    S01 S02 S03 S04 S05 S06 \

    ./atlas/${hemi}.CUSTOM_ROIs.gcs

done

# Create annotations

for hemi in lh rh; do

  for ID in S10 S11 S12 S13; do

    mris_ca_label \

      -orig white \

-novar \

      -t doc/ LUT.txt \

      ${ID} \

      ${hemi} \

      sphere.reg \

      ${hemi}.CUSTOM_ROIs.gcs \

      $SUBJECTS_DIR/${ID}/label/${hemi}.CUSTOM_ROIs.annot

done

done

This lead to a very inaccurate parcellation (see Figure 2), also when we filled the unlabeled region with a dummy label (see Figure 3).

Figure 1. Example for manual segmentation of the 4 subregions (encircled) with deleted original segmentation labels around.

Figure 2. Parcellation example using the trained atlas without dummy label for unlabeled regions.

Figure 3. Parcellation example using the trained atlas with dummy label for unlabeled regions.

Any comments or suggestions on how to deal with our problem would be greatly appreciated. Many thanks for having taken the time to read and reflect

Best,

Nicolas