[Mne_analysis] BEM model: watershed vs. flash

Lin Wang wanglinsisi at gmail.com
Wed Apr 17 17:01:06 EDT 2019
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Hi Eric,

Thank you very much for your clear explanations. I'll try out your suggestions.

Best,
Lin

> On Apr 17, 2019, at 15:18, Eric Larson <larson.eric.d at gmail.com> wrote:
> 
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> 
>> At the beginning, I used the watershed algorithm and MPRAGE images to build the three-layer model. The plot (watershed: https://www.dropbox.com/s/ceyucikgvcpjka9/watershed.png?dl=0) shows that the outer-skull surface is closer to the outer-skin surface, which is very different from what was shown on the MNE documentation webpage here: https://mne-tools.github.io/dev/auto_tutorials/plot_forward.html#sphx-glr-auto-tutorials-plot-forward-py
> 
> Freesurfer's watershed bem strategy is roughly:
> 
> 1. Compute outer skin surface
> 2. Shrink outer skin inward make the "outer skull"
> 3. Compute brain surface (IIRC this is extracted from brain.mgz, which gets masked by brainmask.mgz)
> 4. Expand brain surface outward to make the "inner skull"
> 
> So it's not 100% correct that the outer skull is this way, but it is working as designed.
> 
>> My first question is: which algorithm was used for the plot on the documentation webpage? Should I use flash for the 3-layer model?
> 
> The `sample` dataset has FLASH images, and the BEM surfaces were computed from those.
> 
>> My second question is: is it possible to have a relatively accurate 3-layer model using watershed?
> 
> FLASH should be better than watershed. As to the errors that the watershed creates, I'm not sure. For your subjects that have usable FLASH sequences, you could compute head models using FLASH and using watershed, and compare them, for example how much worse the watershed peak localization is compared to the FLASH ones. You can adapt some of our basic minimum norm benchmarking code if you want. It's also likely someone has already done this, it's probably worth a literature search (I don't know offhand).
> 
>> We have 9 subjects missing the FLASH images. Although I can still build the 3-layer head model using watershed for 8 subjects, I run into this error for one subject:  "the surface inner skull is not completely inside surface outer skull". Is there any easy fix?
> 
> In these cases you can try changing the --preflood / -p parameter in mne watershed_bem. If that does not do it, you can manually run mri_watershed (which mne watershed_bem calls under the hood) with various parameters to fix the output. Or you might have to go farther back in your Freesurfer pipeline to fix the problem. Inner skull not within outer skull can be caused by the brain masking step (part of autorecon1) getting some dura/skull within the brain mask. Refer to the Freesurfer listserv for ideas on how to fix this problem, for example tweaking the mri_normalize parameters via xopts can sometimes help.
> 
> Best,
> Eric
> 
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