I don't have any really good ideas here. If there is a FieldTrip toolbox that
works for SPM5, then you may find that the segmentation in SPM5 gives
slightly better results. However, if your images have poor GM/WM contrast or
poor GM/CSF contrast, then any segmentation algorithm is likely to struggle.
If the GM is invisible by eye, then it is probably also invisible to the
algorithm.
Best regards,
-John
On Thursday 18 September 2008 16:41, aa nn wrote:
> Hi everyone,
> I'm trying to work with my own MRI data for MEG source localization using
> FieldTrip toolbox. FieldTrip toolbox basically calls SPM2 functions for
> segmentation. After I did the segmentation, when I examine the gray matter,
> it seems that fraction of the gray matter was not marked as gray matter.
> They were left out for some reason. For example, part of the visual cortex
> are not included in my gray matter. Since the segmentation is done using
> SPM2, I read the SPM manual a little bit, and, in the manual, it says,
> "5.2.5 Clean up any partitions This uses a crude routine for extracting the
> brain from segmentedimages. It begins by taking the white matter, and
> eroding it acouple of times to get rid of any odd voxels. The algorithm
> continues on to do conditional dilations for several iterations,where the
> condition is based upon gray or white matter being present. This identified
> region is then used to clean up the grey and white matter partitions, and
> has a slight in uences on the CSF partition. If you find pieces of brain
> being chopped out in your data, then you may wish to disable or tone down
> the cleanup procedure." So, I set:
> defaults.segment.write.cleanup = 0;
> When I run segmentation again, it seems to improve the results a little
> bit, but still, I'm loosing some gray matters. How do fine-tune my spm
> parameters (in matlab code) to make it work better? I'm wondering if you
> have any suggestions? Thank you very much for the help! Wei Wang
> Department of Physical Medicine and Rehabilitation
> University of Pittsburgh
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