Hi Bruce,

Thank you very much for your reply. The idea is to create a WM mask that I can use for the denoising step of resting state connectivity analysis. Do you mind if I ask you a few follow up questions?

1 - "our primary cortical segmentation of the wm is not probabilistic."
How is the segmentation of the WM achieved in freesurfer then, if not probabilistic?

2 - "In any case you want partial volume fractions I expect, not posterior probabilities."
Sorry, I'm not sure what you mean by partial volume fractions. In several papers I have read the WM is first thresholded (eg p >.9) to ensure that only WM voxels are included in the mask, which is also eroded. Are the values being thresholded partial volume fractions then, and not probabilities? But if segmentation is done on tissue probability maps (eg like in SPM I think), wouldn't you have probabilities? Or do you mean you have partial volume fractions just in freesurfer?

3 - "I would use mris_fill to create a mask of the WM from the ?h.white surfaces, if you want the most accuracy"
I found more information about the command mri_fill than mris_fill, is there a difference between the two, or can I use both for the same thing?

Sorry for the newbie questions, I am just beginning using freesurfer.

Best
Ben

On Tue, Aug 7, 2018 at 6:08 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Ben

our primary cortical segmentation of the wm is not probabilistic. In any case you want partial volume fractions I expect, not posterior probabilities. I would use mris_fill to create a mask of the WM from the ?h.white surfaces, if you want the most accuracy

cheers
Bruce

On Tue, 7 Aug 2018, Ben M wrote:

External Email - Use Caution

Hi,
I would like to create a mask of the WM for fMRI analysis. I read a previous post in which it was
suggested to get the wm segmentation and erode it, since the result will be exclusively WM. My
question is why is this so? Why can I assume that getting the WM mask from the aseg file will almost
certainly get me high probability WM, >0.9 for example? In most segmentation algorithms we get
posterior probabilities at each voxel, so that we can then select voxels with posterior
probabilities >0.90 for example. Why is freesurfer's WM segmentation so accurate that we do not need
posterior probabilities? Are these very high probabilities somehow already coded in freesurfer's
segmentation algorithm?
Thanks,
Ben

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