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The problem, I think, is in step 2. The filtered func data has had it's 
mean removed (and possibly temporally filtered). You can go back to the 
original data or the example func, but then those won't be intensity 
normalized. You can get the normalization factor from the report.log (or 
recompute it). The pieces and parts are there to do what you want to do, 
you'll just have to put them together.

doug



Paymon Hosseini wrote:

> Dear FSL users, Doug,
>
> mri_segstats gives a table of functional activations calculated by FSL 
> and masked by cortical and subcortical segmentations calculated by 
> freesurfer. i am wondering if there is a way of converting the results 
> of the mri_segstats to "%signal change".
>
> here is what i did:
> step_1)
> as described under "3.0 Creating ROI summaries"
>
> (https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/MapSegmentationsToFunctionalSpace) 
>
>
> i used "mri_segstats --seg aparc+aseg.nii.gz  --nonempty 
> --ctab-default --in subject/stats/cope1.nii.gz --sum cope1.sum.txt" to 
> make a table of mean/min/max activations for each segmented area.
>
> step_2) then i fed filtered_func_data to mri_segstats to find the mean 
> intensity over time for each segmented area:
>
> mri_segstats --seg aparc+aseg.nii.gz  --nonempty --ctab-default --in 
> filtered_func_data.nii.gz --sum mean.sum.txt
>
> step_3) then i tried to normalize the mean activations i found in 
> step_1 by the mean intensities found in step_2 to get the "% signal 
> change".
>
> to double check the results, i used featquery to calculate the " % 
> signal change" for two segmented areas.
>
> here is the problem:
> the results i get from step_3 are NOT close to the "%signal change" 
> results that  featquery creates for the two areas i checked 
> (hippocampus and amygdala).
>
> i am wondering if you can give me some insights on how to calculate 
> the "%signal change" correctly via mri_segstats.
>
> thanks
> paymon
>
>

-- 
Douglas N. Greve, Ph.D.
MGH-NMR Center
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Phone Number: 617-724-2358 
Fax: 617-726-7422

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