Dear Alberto,
if you replace the lesions with NaN these voxels will not be used for spatial normalization, which is probably exactly what you intended. However, there is another way to deal with WM lesions that is described in:
http://dbm.neuro.uni-jena.de/pdf-files/Schmidt-NI11.pdf
The Lesion Segmentation Toolbox is filling the detected lesions with the surrounding tissue values which might be a better way to deal with this issue. I would give the LST toolbox a try:
http://dbm.neuro.uni-jena.de/software/lst/
Regards,
Christian
__________________________________
Christian Gaser, Ph.D.
Departments of Psychiatry and Neurology
Friedrich-Schiller-University of Jena
Jahnstrasse 3, D-07743 Jena, Germany
Tel: ++49-3641-934752 Fax: ++49-3641-934755
e-mail: [log in to unmask]
http://dbm.neuro.uni-jena.de
On Tue, 8 May 2012 02:51:22 +0100, Julio Alberto González Torre <[log in to unmask]> wrote:
>Hi.
>
>My question is about VBM8.
>
>We have a set of images from T1 of multiple sclerosis patients, and a set of masks with white matter lesions manually segmented for each subject. We are trying to insert this information in the VBM8.
>
>We found one possible solution: to take the T1 images and setting their respective lesion voxels to NaN value. We think that this method maybe correct, because it makes VBM to ignore this voxels from the segmentation.
>
>The question is: this method is correct? The result will be valid? Is there any documentation or publication about this issue?
>
>Too many thanks,
>
>Alberto.
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