SPM list,
I am sorry id this has been gone over in the past, but I recently read the
paper on VBM methods by Ashburner and Friston and have a couple of
questions.
1) The paper makes quite a point about having high resolution MRI scans, and
yet the methods state that the segmentation is performed on the normalized
images. Would not it be better to segment the raw images that are in 1x1x1mm
voxels than to use the images that have been re-sampled into 2x2x2mm voxels?
Is there a higher resolution template image that can be used for this
specific application?
2) The smoothing of 12mm seems somewhat high to me when theoretically, the
resolution of the data is 1m FWHM (in the raw form or 2mm FWHM normalized as
per the paper) is the 3x voxel size no longer valid for this approach?
In the end I guess I have worked out a different pre-processing method and I
was wondering if I could get some input on it's validity.
1st segment the high resolution MRI scans.
2nd smooth the gray matter segments with a 6mm Gaussian kernel to better
facilitate normalization.
3rd normalize the raw image to the template space and bring the smoothed
gray matter image with it.
4th the smoothed gray matter image needs smoothed once more in order to
remove the effects of the deformation of the Gaussian field that occured in
the normalization step (6mm again). In the end this would leave the images
with a 8.5mm resolution.
continue statistical analysis as per paper.
any thoughts on this will be appreciated.
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