Hi, Philipp-

Great, thanks. *That* shows your initial overlap, with your anatomical (that has no obliquity) and the EPI *with its original obliquity applied*. That is a reasonable starting point for alignment. I would put those datasets into afni_proc.py, sticking with the "lpc+ZZ" cost function for EPI-anatomical alignment.

Going back to the original point, you typically start an FMRI input with an anatomical dset and one or more EPIs.
+ If the anatomical has obliquity, it will generally be useful to use those few lines to get rid of it from the start (preserving the original location).
- in some cases, one might just deal with the anatomical's obliquity considerations by initially *applying* the obliquity with "3dWarp -deoblique ..", but the downside of that is that the image will become inherently/slightly blurred in the regridding process, hence the preferred step of deobliquing without regridding but preserving coordinate origin.
+ But if the EPI has obliquity, which is more common, you should generally be OK leaving it in. afni_proc.py will deal with it appropriately internally (applying the obliquity as needed).
+ using @djunct_overlap_check can quickly verify that initial overlap will be OK (or not)
- if neither input has obliquity, only one image is output, and check that initial overlap/alignment for reasonableness
- if either input has obliquity, then 2 images are output: one ignoring obliquity values, and one applying all of them (the *DEOB* one). The *DEOB* one would be the one to focus on for judging alignment/overlap quality.

--pt



Edited 1 time(s). Last edit at 12/13/2022 07:14AM by ptaylor.