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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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Oh I see. But it so happens that when I do the deobliquing with the gridset option included, the posterior part of the brain gets clipped off in most of the patients (can't figure out why though) and that's something I can't afford to have, when I am doing my group comparison.
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sush
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AFNI Message Board
Ah yes, sorry I forgot to mention this, but I've been using FSL's MELODIC ICA toolbox for pre-processing. So after despiking my images the toolbox does the following pre-processing steps for me:
brain extraction->spatial smoothing->high-pass filtering-> registration to the standard MNI 152 template
I am hoping that the registration step would be good enough for aligning
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sush
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AFNI Message Board
I am actually using python's Nipype which includes both FSL and AFNI functions, the pre-processing pipeline is:
motion correction using MCFLT-> Despiking -> high-pass filtering -> smoothing. And after the pre-processing I am generating the activation maps.
Aligning and co-registering of my functional images were not something that I intended to do, but if it's a solution
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sush
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AFNI Message Board
Unfortunately no other pre-processing step in my pipeline takes care of the error. I shall try out your suggestion of co-registering and aligning. Thank you for the suggestion.
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sush
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AFNI Message Board
Ah yes, that works. Thank you. But using gridset presents its own set of problems such as clipping off the posterior part of the brain (at least that's the case for my dataset). Deoblique without gridset presents no "clipping" problems whatsoever but each subject has different dimensions after 3DWarp and for the task of prediction, the changing of dimensions wouldn't bode well
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sush
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AFNI Message Board
Hello AFNI experts
I am doing a bit of pre-processing on functional fMRI images using Nipype-AFNI and I always get a warning saying " oblique dataset is ... degrees away from the plumb, consider using 3DWarp", but when I do use the 3dWarp command on my functional scans, the dimensions of the resulting fMRI image is different from the original. For instance my original data has the di
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sush
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AFNI Message Board