Steve, if you're reading this could you comment? Feel free to do some
FSL sales pitch.
I'm guessing that the low quality T1 has the same (phase encode
direction) distortions as the EPI data, and that the additional step is
in order to correct some of these distortions. It is easier to obtain a
more accurate registration if the relationship between the intensities
in one image are simply related to the intensities of the other - so
nonlinear matching a T1 weighted to another T1 weighted image is easier
than matching a T2* weighted to a T1.
If the transformation is indeed a nonlinear one, then there is no easy
way of doing this within SPM. If it is a rigid-body, then the
Coregister button should do a reasonable job. Coregistration of the low
quality T1 and the EPI may not be necessary if the images were acquired
in the same session and there was no subject motion.
Best regards,
-John
I have a question. I have seen papers and spoken with people using
FSL,
who do the normalization process in several steps. First, they
coregister
the low-quality T1 image (that is taken at the same time and in the same
space as the functional data, and thus will coregister much better) to
the
functional image. Next, they determine the paramaters of the non-linear
transformation from the low-quality T1 to the high-quality T1 (eg
MPRAGE)
and from the MPRAGE to the standard-space template. They then multiply
those two transformation matrices (low quality T1 -> MPRAGE -> template)
and
apply the parameters to the functional images in order to normalize them
to
standard space. Hence, my question is: how would I do this in SPM? I
can
do each transformation and apply the parameters separately, but warping
the
functional data twice will create more opportunities for the data to be
mishandled; I would prefer a single warp with the combined parameters.
Thanks for the help!
Daniel Simmonds
Developmental Cognitive Neurology
Kennedy Krieger Institute
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