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When I run these through fslstats on a sample subject, I get: #1. [fsl@fslvm6 stats]$ fslstats -t all_FA_skeletonised -k MiddleCerebellarPeduncle -m 0.084332 #2. [fsl@fslvm6 stats]$ fslstats -t all_FA_skeletonised -k MiddleCerebellarPeduncle -M 0.507225 #3. [fsl@fslvm6 stats]$ fslstats -t all_FA -k MiddleCerebellarPeduncle -M 0.404983 #4. [fsl@fslvm6 stats]$ fslstats -t all_FA -k MiddleCerebellarPeduncle -m 0.380390 It seems that using skeletonised FA data with the mask resulted in abnormally low values if nonzero-voxels were counted, and normal if left out. When I ran fslmeants, it counted nonzero voxels and gave me the same distorted value as in #1. What I can't tell here is which of these other methods are showing the truest estimate of FA in these regions? Or is there a better way to approach this entirely? On Thu, Feb 6, 2014 at 10:27 PM, Chris Watson < [log in to unmask]> wrote: > If you replace "all_FA" with "all_FA_skeletonised", that should only > give you FA in the peduncle for only those voxels that are also in the > skeleton. > > On 02/06/2014 08:01 AM, Evan Stone wrote: > > Hey all, > > What would be the best way to extract regional DTI data?! I have skeletonized diffusion data for all major parameters (FA, MD, RD, and AD) and have created masks for the CBM-JHU atlas for each region/threshold. Should I use skeletonised data despite the fact that the masks are not skeletonised? I have used, for example, fslmeants -i all_FA -o MiddleCerebellarPeduncle.txt -m MiddleCerebellarPeduncle.nii.gz...should I use fslstats instead? Should I count or exclude non-zero voxels if I do? > > HELP! :-) > > -Evan > > > > >