Dear FSL experts,
I'm using Featquery to compute percent signal change from various regions of
interest. I've first run Featquery with the default settings, which were to
use the inverse of non-linear registration from highres2standard and the
inverse of the affine transformation from example_func2highres. However, I
noticed that several subjects (I still need to check the others), the
resulting mask transformed from standard to native EPI space is excessively
small, 2 or 3 voxels at best, sometimes empty, while the volume of the mask
in standard space is 528 mm2 (66 voxels). I checked the
example_func2standard registration and it looks fine.
To compare, I manually registered the standard mask to EPI space using only
the inverse of the affine transformations from example_func2highres and
highres2standard, using the default interpolation method and
post-interpolation threshold value. Now, I obtain a 72 voxel mask (2812 mm2)
that is even bigger than the original one in standard space...
At this point I'm a bit confused as to why the mask obtained with linear
"back-registration" is so big (might need to adjust the post-interpolation
threshold?), but what I really don't get is why the results between the 2
registration methods are so different.
Any hint as to what I might have done wrong would be greatly appreciated!
All the best,