Hi Philipp,
Overnormalization is less likely in SPM2 than in SPM99.
There is a cutoff-value in the defaults (which you could
change yourself to an even more conservative value)
that prevents the normalized brain to extend beyond
the area covered by the scans.
Using the EPI template should therefore work ok.
However, using the EPI-template can introduce
spatial insecurities of approx. 2 cm! We tested both
ways of normalization (using T1 or EPI template)
with a tumor data set - with this quite alarming result,
especially if you are interested in small brain areas
(hippocampus and the like).
If coregistration fails (it does in 50% of all cases with MI
at least for us) you can work around this in three ways:
Use a deskulled anatomical
(but don't use this image for normalisation!
so copy the .mat file gained and rename it so it applies
to the original anatomy)
Use the coregistration in SPM99 (the segmentation approach
is worth (several) tries, if MI fails. If MI fails, it will fail
consistently
whatever the starting parameters and default options -
at least to my experience. When Segmentation fails you get at least
different results for different starting parameters (.mat file).
If you get a near but not perfect match, e.g. the funcs 2mm lower
than the anatomicals, use display to enter the displacement value
by hand and reorient the anatomical.
Hope that helps,
Best,
Anja
Dr. Anja Ischebeck
Innsbruck Medical University
Clinical Department of Neurology
Anichstrasse 35
A-6020 Innsbruck - Austria
tel.: +43 (0) 512 504 23661
>>> Philipp Saemann <[log in to unmask]> 07.10.2005 01:49 >>>
Hi,
for an fMRI series which does not cover the whole brain (e. g. 20
slices 4 mm
thick), how is spatial normalisation best achieved?
Can object masking (be recommended, e. g. a binary mask of the volume)
to keep
the influence of the missing parts and the border zones low ?
Should the starting position be optimized manually (SPM2)?
(Coregistering on T1 did not work properly using MI, otherwise we would
have
used this option)
Grateful for any hints on this,
Philipp
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