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Subject:

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

From:

"Stewart, Peter" <[log in to unmask]>

Reply-To:

Stewart, Peter

Date:

Tue, 13 Feb 2018 13:09:58 +0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (1 lines)

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



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

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

Sent: Monday, February 12, 2018 1:48 PM

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

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



Hi Peter,



lurking, indeed ;)



In any case, you could use the CerebroMatic to generate TPMs for your population. The upper age range is, I think, 900 months, so that may be a problem, but in general, that might be the most straightforward way. 

As you have noticed, the correction is built-in.



In addition to the CerebroMatic generating custom TPMs, I have now used it to generate custom DARTEL templates in the same fashion. I.e., you specify the demographic parameters of your population and let the toolbox do the rest, resulting in your very own custom DARTEL templates.



There is a paper out on this just recently, appropriately called "A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age" which is freely available at

https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1016%2Fj.dib.2017.12.001&data=02%7C01%7Cpstewart1%40geisinger.edu%7C8d47caf9d1b9434ca7c308d572492368%7C37d46c567c664402a16055c2313b910d%7C0%7C0%7C636540580829414648&sdata=7o51cWEJ7jchLjS4eO4dZsTF21yvaZx%2F9OPzAYXO1Zw%3D&reserved=0



Now that the advertising is over, making tissue volumes sum to 1 is actually not that hard if you still want to do it yourself. You need to ensure that the sum of each voxel across all classes is 1, which you can achieve (after removing 0's) by summing over all classes as in



V = spm_vol(spm_select);

vol = spm_read_vols(V);

vol(vol==0) = eps;

corr = ones([size(vol,1) size(vol,2) size(vol,3)]) - sum(vol, 4);



and then you need to incorporate that information into the existing volume, by combining it with the last class (which is a bit dirty but since the last class is background anyway, it shouldn't matter), as in



vol(:,:,:,end) = vol(:,:,:,end) + corr;



upon which you now only need to write the file, as in



[p, nm, e, ~] = spm_fileparts(V.fname);

V.fname = [p filesep nm '_corrected' e]; spm_write_vol(V, vol);



or something along those lines. You may want to check that this actually works because it's already late for me, but in principle, it should.



Hope this helps,

Marko



Stewart, Peter schrieb:

> Hi Everybody,

>

>

>

> Thank you all in advance for the invaluable information on this list. 

> I have learned so much from reading all your conversations. I would be 

> greatful for any help that you can give me with a project I'm working 

> on. Marko, I'm hoping you are lurking out there because I am sure you 

> know the answer. The situation is this....

>

>

>

> I had the idea to create a set of custom TPMs and DARTEL templates for 

> older individuals with mild cognitive impairment and mild Alzheimer's 

> disease. I had planned to use CAT12 to do priorless segmentation of a 

> large number of individuals as in Wilke et al.'s excellent 

> Cerebromatic paper. Then, I had planned to average the DARTEL 

> registered CAT12 tissue classes from the subjects together to create 

> TPMs. Looking over preliminary results, there are many zero voxels in 

> the resulting TPMs and the probabilities across the 6 tissue classes 

> sum to 1.1 or more in many cases. How can I go about correcting these, 

> such that the tissue probability maps I create will add to a total 

> probability of 1 across the tissue classes and there are no zeros? I 

> know that this must be the case to use TPMs with SPM. I have been 

> going through the cerebromatic code to see how this was achieved by 

> Wilke but I'm having a hard time understanding it. Thanks in advance, I appreciate the help.

>

>

>

> Regards,

>

> Peter

>

>

>

> Peter V. Stewart, Psy.D. | Staff Neuropsychologist | Assistant Director:

> Clinical Neuropsychology Postdoctoral Training Program | 

> Neuropsychology Internship Coordinator | Geisinger Health System | 

> [log in to unmask] <mailto:[log in to unmask]> et al.,

>

>

> IMPORTANT WARNING

> ----------------------------------------------------------------------

> --

>

> 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, 

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> you have received this message in error, please delete all electronic 

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> Center to retrieve the encrypted e-mail.

>



--

____________________________________________________

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%7C8d47caf9d1b9434ca7c308d572492368%7C37d46c567c664402a16055c2313b910d%7C0%7C0%7C636540580829414648&sdata=xv8oIb3SNxo3%2FoIStXpN8AvtakB4DI1GZGzEXhTwvbo%3D&reserved=0

____________________________________________________



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