Hi @lzjwilliams and @seanfitz, thanks again for your work!
I’ve tested the latest version, but it looks like the vertex correspondence issue is still present. Just wondering if there are any updates on this—has a fix been implemented or is it currently being looked into?
We suggest you run the deep learning pipeline instead. It’s quick and generalizes better than the old one.
Hi @EmmaR, thanks for your reply! I will follow your suggestion and use the deep learning based pipeline instead.
Hi @leonardozaggia, where you able to confirm if the DL pipeline solves the correspondence issue? Thank you!
Hello @EmmaR and @leonardozaggia. Unfortunately, building the cortical surfaces using the deep learning piple does not solve this issue, the vertex correspondence error keeps showing up.
Hi @diegoder, thanks for your update. So far, as a temporary workaround I have replaced the -ribbon-constraint option with the -trilinear method for volume-to-surface mapping.
In this setup, I used the mid-thickness surface as the target for projection.
I’m not entirely sure if this is an appropriate substitute, but it seems to work for now — I’d be curious to hear if others have insights or suggestions on this approach.
What do you mean by vertex correspondence issue? As the deep learning pipeline derives everything from one template with constant mesh topology then all the files must have the same number of vertices. Indeed, I just got one of my team to double check this for me.