Thank you for correcting my misunderstanding of 3dvolreg's function. I misread the afni_proc.py documentation.

Thank you as well for pointing me to @snapshot_volreg. This is an amazing tool! I tried this out on one processed image that was result of linear affine and nonlinear transformations on the same scan.

I ran:

@snapshot_volreg anat_final.SUBJECT_ID_10000000+tlrc   \
                               final_epi_vr_base+tlrc

The resulting jpegs are attached here. I wanted to ask how to interpret the images. The large lateral ventricles and sulci on superior parts of the brain both look fine (although the nonlinear is slightly better in my opinion).

But is there something fundamentally wrong with the registration? In the top row, I see lines (circles) outlines from the final_epi_vr_base+tlrc file. Is this typical?

This is from the documentation for @snapshot_volreg states:

"The edges from a typical EPI dataset are usually broken up and
do not completely outline sulci, ventricles, etc.  In judging
the quality of alignment, I usually start by looking at the
outlines of the large lateral ventricles -- if those are very
wrong, the alignment is not good.  After that, I look at the
sulci in the superior part of the brain -- if the EPI edges
there seem to be mostly aligned with the sulci, then I am
usually happy.  The base of the brain, where lots of EPI
dropout happens, often does not not show good edge alignment
even when the rest of the brain alignment looks good."

It does not provide references to circles that can be seen in both the linear affine and nonlinear warps. At the same time, the circles are towards the inferior part of the brain in both cases, with documentation stating that EPI dropouts occurring at base of the brain.

Thank you again!



Edited 2 time(s). Last edit at 07/06/2017 09:19AM by cmehta.