Is there any indication that there has been any sort of problem with how
the tissue probability maps are overlayed on the images (ie check that
the initial affine registration has worked). If there is a problem,
then it should be extremely obvious - although sometimes people don't
appear to notice. More accurate initial registration may be required
(ie via the Display button).
Other than that, I'm not really sure what the problem is with your data
and why it doesn't seem to fit the SPM5 segmentation model so well.
Best regards,
-John
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
On Behalf Of Kenneth Rando
Sent: Friday, July 06, 2007 7:41 PM
To: [log in to unmask]
Subject: [SPM] posterior probabilites in SPM5 segmentation
Hello Listmembers,
I have previously used SPM2 sucessfully, but I am using SPM5 for the
first
time to perform a VBM analysis. It is also the first time that I am
using
3T scanner data. By comparison to our earlier 1.5T data the gray
matter/white matter contrast is lower. Inhomogeneity has also been a
problem with this data. Reducing the spatial frequency of the bias
correction in the Segment function has helped, based on visual
comparison
of segmented data to the original scans.
Compared to my SPM2/1.5T data results, I have noticed that the voxel
posterior probabilites in the gray matter segments are lower. My SPM2
gray
matter segments contained mostly probabilities near 1 or 0 (which I
expect,
if I understand some of the published or SPM list discussions of
segmentation). The cortical regions at the edges of the image, where
the
inhomogeneity has been a problem, have values more in the range of
.75-.85
(perhaps less). I can't fully correct the inhomogeneity problem, it
seems,
without inaccurately reclassifying gray matter as white matter. Does
SPM5's Unified Segmentation contribute to the greater variability in the
probability values? More importantly, can I still expect valid
estimates
of group effects?
Thanks.
Ken
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