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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