Dear Kiyotaka,
you should keep in mind that the values in the segmented images are reflecting the probability of being grey matter. So, if you run a formula of i1>0.01 means, you take all voxels with a probability of being grey matter of 1%, that's rather low.
So, it depends, what are you going to do. I'm running some analyses tools, where I need binary grey-matter images, as well. There I usually use 30% or 50% (or even more), i.e. i1>0.3 or i1>0.5 etc. But, this threshold crucially depends on the quality of the segmentation, i.e. the quality of your original T1 images. In my case, I'm running a sequence (on a 3T scanner) with a very good grey-white matter differentiation, which allows me to go to even higher thresholds.
So, I would start with 30%, i.e. i1>0.3
Perhaps, John has other recommendations.
Good luck,
Karsten
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Karsten Specht, PhD
Department of Biological and Medical Psychology
& National Competence Centre for functional MRI
University of Bergen
Jonas Lies vei 91
5009 Bergen
Norway
Tel.: +47-555-86279
Fax: +47-555-89872
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http://fmri.uib.no/
> I'm interested in the optional binarization step in VBM John mentioned in Human
> Brain Function 2nd ed. It says,
>
> "A further possible step after segmentation would be the binarization of the
> resulting tissue class images. Many tissue classification methods produces
> images where each voxel is the a posteriori probability that that voxel should
> be assigned to a particular tissue type according to the model. These
> probabilities are values between zero and one. Binarization would involve
> assigning each voxel to its most likely tissue class."
>
> I have been trying to implement this step of binarization, but I'm struggling
> with setting threshold for this binarization. This is because non gray matter
> regions have some values other than zero (such as 0.01, 0.03 etc), so simply
> performing Imcalc i1>0 results in covering other regions than gray matter. I
> change the threshold manually right now (eg i1>0.04, which seems to be pretty
> good to me), but I think there has to be some good formula to set the threshold
> to extract just gray matter. And also I'm wondering if there is a way to compare
> the segmented image with the binarization image and see whether right regions
> are binarized or not. Could you please let me indicate how to do that? I would
> be grateful for any suggestions.
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