Christian - Thanks for clarifying!



Marko - Thank you, once again, for your help. The updated version of COM you provided works like a charm and produces some pretty and very smooth looking TPM. I will play around with it. Thanks for clarifying that your code was intended for 4D images...that would be the easier way to implement it! I have a way of making things harder than they need to be. As for the segmentations output by CAT12 having values greater than 1, you are right! I must have clicked something wrong (e.g., thus enabling molduation). I re-did some of the segmentations and there are in fact no values over 1.0, so this was my mistake. Will have to look over the batch scripts to see where I went wrong. Thank you also for the "dirty" way to functionally disable DARTEL. All very helpful. It is gracious of you and Christian to share your time!  



Regards,

Peter



-----Original Message-----

From: Marko Wilke [mailto:[log in to unmask]] 

Sent: Tuesday, February 13, 2018 1:03 PM

To: Stewart, Peter <[log in to unmask]>; [log in to unmask]

Subject: Re: [External] Re: [SPM] Creating tissue probability maps, how to make all classes sum to 1 with no zeros



Hi Peter,



> First of all, thank you so much, I am standing on the shoulders of 

> giants



As are we all.



! 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.



Glad to hear. My code snippet assumed you already have the TPM in a 4D format, which does not seem to have been the case, but you worked yourself out of this.



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?



Let us put it this way, it is a dirty solution from a mathematical elegance point of view, but I have never seen this to cause an issue.



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?



This should not actually be the case. One reason I could think of is that you are still using some kind of modulation (which you shouldn't) or that some post-hoc filtering leads to this. You could simply replace all values exceeding 1 with 1.



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?



I would be careful with treating all classes equally as many of the optimizations within CAT12 are specially applied to GM and WM, and not to the other classes. Making sure they sum to 1 is therefore particularly important, but I would rather lay the burden on the less-relevant classes (i.e., 6) than fiddle with the prime classes (i.e., 1 & 2).



> 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



This is an error which I had not foreseen in the early days as there is now a Matlab function with that name that previously didn't exist (introduced only in R2017b, I think). The error comes from the toolbox calling the original function, not the one from Damien Garcia I recommend. To avoid this, I now include the function in the toolbox and and renamed it to avoid confusion. I can send you that latest version off-list and will make sure it is updated soon on the website.



> 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.



Another way around it would be to use Gaussian, not median filtering, or to put the Damien Garcia function higher up in Matlab's search path.



> 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?



I hacked cat12, much to Christian's dismay :) I would actually have to look how I did this (it was several workarounds) but an effective (but yet again dirty) shortcut is to set all DARTEL iterations to 1 and all stabilizing parameters to Inf. This will not formally, but effectively disable DARTEL processing.



> Thank you so much for your help, it means a lot to me!



Glad it works for you (somehow ;)



Cheers

Marko



--

____________________________________________________

Prof. Dr. med. Marko Wilke

  Facharzt für Kinder- und Jugendmedizin

  Leiter, Experimentelle Pädiatrische Neurobildgebung

  Oberarzt der Abteilung Neuropädiatrie

  Universitäts-Kinderklinik



Marko Wilke, MD, PhD

  Pediatrician

  Head, Experimental Pediatric Neuroimaging

  Consultant in Pediatric Neurology

  University Children's Hospital



Hoppe-Seyler-Str. 1

  D - 72076 Tübingen, Germany

  Tel. +49 7071 29-83416

  Fax  +49 7071 29-5473

  [log in to unmask]



  https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.medizin.uni-tuebingen.de%2Fkinder%2Fepn%2F&data=02%7C01%7Cpstewart1%40geisinger.edu%7Cb7aaf74f6651482d470408d5730c0317%7C37d46c567c664402a16055c2313b910d%7C0%7C0%7C636541417804946145&sdata=fHreAtlTda065rHoIxuE%2FbLAhVyPgOBNADtPHos0ktA%3D&reserved=0

____________________________________________________





IMPORTANT WARNING: The information in this message (and the documents attached to it, if any) is confidential and may be legally privileged. It is intended solely for the addressee. Access to this message by anyone else is unauthorized. If you are not the intended recipient, any disclosure, copying, distribution or any action taken, or omitted to be taken, in reliance on it is prohibited and may be unlawful. If you have received this message in error, please delete all electronic copies of this message (and the documents attached to it, if any), destroy any hard copies you may have created and notify me immediately by replying to this email. Thank you. Geisinger Health System utilizes an encryption process to safeguard Protected Health Information and other confidential data contained in external e-mail messages. If email is encrypted, the recipient will receive an e-mail instructing them to sign on to the Geisinger Health System Secure E-mail Message Center to retrieve the encrypted e-mail.