AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

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Bob Cox
March 29, 2018 02:25PM
I have used 3dQwarp with the '-emask' option. Here, 'e' means "exclude" -- that is, the option provides a mask of voxels NOT to use in the alignment process. There are some details you have to understand to use this properly:

  1. You have to learn to draw the exclusion mask over the subject's image dataset, which isn't hard but takes a little practice. This is done via the AFNI "Draw Dataset" plugin.
  2. The exclusion mask is in the base (template) space, so you have to register the template to the subject's dataset, and then apply the inverse of the warp transformation to get the subject's dataset into the template space.
  3. You probably have to skull-strip and 3dUnifize the subject's dataset ahead of 3dQwarp-ing (to match the template). Scripts @SSwarper or auto_warp.py can do all of these things for you, including the warping, but aren't appropriate since they don't allow use of an exclusion mask. So you have to manually assemble the correct processing stream.
I don't think this is HARD, but then again, I wrote the software and understand how it works better than anyone, so perhaps I'm biased.
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Subject Author Posted

Normalizing brain image with lesions

lzhyoung March 29, 2018 03:38AM

Re: Normalizing brain image with lesions

Bob Cox March 29, 2018 02:25PM