Hi Bob and thanks!

I did some further digging. I created an average map of the "mask_WMe_resam +tlrc" file for ca 30 subjects from both the group we overall expect to have more atrophy issues and one group of healthy adolescents. We then compared them to each other and to the WMe_resam that we get from running 3dSeg + 3dmask_tool + 3dresample on the TT_N27+tlrc template.

What we can say is this:

1. The WMe_resam that you get from the TT_N27+tlrc set is pretty good. The loss in Corpus Callosum is due to the re-sampling.

2. Overall (both healthy adolescents and alcoholics with expected atrophy) labels some sub-cortical structures as WM, e.g. Putamen (see the images below).

3. Corpus Callosum is an example where the healthy adolescents overall get a more correct WM labelling and the patients gets an extended WM segmentation where GM dorsally of Corpus Callosum gets labelled at WM. Look at the diff_map where red means patients have a higher average white matter value and blue means that the value was higher in the healthy group average WM map.

4. By overlaying the diff_map over the WM segmented out of the TT_N27+tlrc tempalte we can see that the blue "healthy" voxels better overlap with the white TT_N27_WMe_resam underlay and that the red "patient" voxels more often extend the WM structures.

5. Difficult followup question: How could these findings explain the results I posted previously? Do you recommend not running anaticor on these patients? Since the WM mask covers all of Putamen in many subjects we might loose interesting signal from there? Also true for the healthy group though but not as bad.

Images: attached as a google drive link since there is a limit of 2 files to uppload and you cant upload .zip files:

[drive.google.com]

TT_seg_resam = Segmentation preformed on the TT_N27+tlrc template where I resampled to the resolution of the EPIs in our experiment. The segmentation seems to be good.

healthy_mean = 3dmean run on the mask_WMe_resam of 30 healthy subjects (values 0-1) overlayed on TT_N27+tlrc. Looks decent but it covers a lot of Putamen and some GM areas.

patients_mean = 3dmean run on the mask_WMe_resam of 30 alcoholic patients subjects (values 0-1) overlayed on TT_N27+tlrc. It seems like it tries to categorize more GM as WM and Putamen is more often classified as WM.

mean_diff = mean_patients - mean_healthy. Red means that the region is overall more commonly classifed as WM in the patient group and blue means that the region is more commonly classifed as WM in the healthy group. Putamen and the GM dorsally of Corpus Callosum is clearly more often labeled as WM in the patient group.

TT_WMe_resam_diff = The difference map overlayed over the the WMe_resam of the TT_N27 with lowered opacity. Here it is quite clear that the blue "healthy" voxels better overlap with the white TT_N27_WMe_resam underlay and that the red "patient" voxels more commonly expand over the TT_N27_WMe_resam underlay, indicating that more GM is clasified as WM in the patients.



Edited 1 time(s). Last edit at 03/06/2018 09:51AM by Robin.