Hi,
what I would do:
- To average wcXX images to get the mean image of each tissue. You can do this by imcalc: select all images to average, expresion mean(X) and Data matrix: Yes, read
- To use spm_imcalc to look for those voxels having greater probablitity of being GM: select mean images of tissues use expresion: (i1>i2).*(i1>i3).*(i1>i4).*(i1>i5) (if you saved wc4 and wc5) or (i1>i2).*(i1>i3).*(i1>0.1) if you didn’t. Images are supposed to be selected in the proper order 1->5. Data Matrix: don’t read
This procedure will give you a customized GM mask of your sample. I would not recommend to use AAL for this. AAL GM mask is made from one single subject and could be non-suitable for your sample. In case it were necessary you could adapt GM mask to fMRI images images by reslice option from coregister menu using NN interpolation
Best
Carles
El 12/08/2015, a les 18.11, Mike <[log in to unmask]> va escriure:
> Hi,
>
> To reduce global multiple comparison issue, I want to confine my group analysis contrasts in gray mater (GM) only, i.e., excluding voxels in white mater and CSF. To this end, I want to get an average GM mask from all my subjects.
>
> My strategy is to do "Segment" in spm8 for each subject's T1-weighted images. In "Grey Matter," I selected "Native+Modulated+unmodulated." After finishing, I got wcxxx and mwcxxx files, both of which are in standard 2x2x2 space, suggesting they are normalised to standard template. Then I plan to average all subjects' wcxxx (or mwcxxx) files to get an average GM mask from all my subjects.
>
> Can anyone tell me which file should I use? wcxxx files or mwcxxx files?
>
> Or, is my strategy to get an average GM mask from all my subjects appropriate?
>
> Thanks.
> Mike
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