Dear Peter,
CAT12 can only save the images with DARTEl registration (or affine registered). The old approach with the unified segmentation registration is not working anymore.
Best,
Christian
On Tue, 13 Feb 2018 13:09:58 +0000, Stewart, Peter <[log in to unmask]> wrote:
>Marko,
>I apologize for the long e-mail. First of all, thank you so much, I am standing on the shoulders of giants! Your code is very helpful, I had to modify it by using the following:
>Vn = squeeze(V(n,:))
>Voln=squeeze(vol(:,:,:,n0)
>Then feed the individual images into spm_fileparts and spm_write_vols one at a time (it was complaining when I tried to do it with the full array of all 6 tissue class images at once). I will need to write some loops so it's not tedious to do for each of the 6 tissue classes, but it seems like it should work. The output seems to make sense. Just to check my understanding, this means that classes 1 - 5 (in a 6 class solution) are unchanged, other than replacing the zeros with eps() and all the "junk" is simply added into the background class (class 6). This means that there are negative numbers in the background class. For some reason, I had assumed that having negative numbers would be an issue but apparently it isn't for SPM? Obviously you achieved very good results with this strategy in your paper. There are also some probabilities that are greater than 1, for instance, in the white matter class many of the CAT segmentations have "1.1" as a value for voxels, I assume that this is also unproblematic for SPM? Would it make any difference to, say, replace 0's with eps(), then scale all tissue classes 1-6 from 0 to 1 on a voxel by voxel basis across classes, then do the subtraction from the background class as implemented below to make sure they all sum to 1?
>
>In terms of advertising, I HAD considered using cerebromatic, not only to generate priors for my population but to derive new regression parameters from the CAT12 segmentations of my population in order to incorporate additional predictors into the model that may be of interest in an older population of mci and demented individuals. Every time I try to generate TPMs using cerebromatic, it gives me the following:
>
>Error using medfilt3
>Expected [m n p] to be odd
>
>And then kicks out a number of other errors. I tried reinstalling with a fresh version of matlab and SPM to see if it was a system specific bug, but it has done this on two different computers. Any idea what is going on or how to fix? I had thought to play around with the filter size in the com_gen script and see if that fixes it but hadn't gotten around to it yet.
>
>ONE final question: I was trying to get CAT12 to output tissue probability maps using unified segmentation non-linear registration only (i.e., not DARTEL). When I change the cat_main code to be "do dartel = 0" it won't output warped images. It says in the CAT12 manual that it IS capable of generating normalized tissue maps using unified segmentation normalization only but I can't seem to find where that option is...how did you do this in your paper?
>
>Thank you so much for your help, it means a lot to me!
>
>Very best,
>Peter
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