Yes, we did carefully check all major dropout-susceptible regions of the brain and still found that the GE AP/PA 'way' somehow produced more 'complete/better looking' EPIs. The output we get from the GE AP/PA looks quite reasonable, whereas the SE AP/PA produced scans looking actually a bit worse with more dropout where we didn't suspect it. We got the same kind of result for four different kinds of EPI scans, making me thing that either our SE AP/PA protocol isn't optimal in some way (or I am just doing something wrong in the analysis).
But I still wish to figure out what's the deal with our SE AP/PA scans (se_ep2d based), exactly because in theory SE approach should work better due to absence of signal dropout in the AP and PA scans.
In our analysis, we just used basic topup to get the unwarping data - then did applytopup to unwarp functionals - being careful about orientation issues. Just as written in the tutorials. We didn't mask or anything.
Could I possibly as a test obtain one of your SpinEchoFieldMap AP/PA scans as well as a functional (and how it should be looking once it's unwarped)?
Thanks and best wishes