Hello Doug,
I have used the gtmseg with --keep-cc flag and the corresponding ctab files showed the labels but the mri_gtmpvc step failed. **** Loading seg for gtm gtmseg.mgz Loading seg ctab gtmseg.ctab Reading gtmseg.lta Replacing 18 ERROR: CheckSegTissueType() no entry for seg 192 Failed tissue type check **** My objective is to use the combination of all CC's as a reference region and obtain the PVC results, which would be listed in gtm.stats.dat
Also, I read in the previous email discussions that the default ref-region Pons is 'PVC'ed'. So if I want to calculate the SUVR with another ROI as a reference region, would it be OK take a ratio of the ROI's in gtm.stats.dat table.
Thanks, Pradeep
On Mon, Jan 11, 2016 at 9:25 AM, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
If you want to use partial volume correction, then you are better off using mri_gtmpvc with the bbr registration, something like
- To start, run
gtmseg --s subject
This will take a couple of hours and produces some files needed for GTM PVC (which is used for GTM, MG, RBV).
- You'd then register the PET to the anatomical with bbregister
(probably with --t2 weighting). Make sure to save the output as an LTA (--lta). I usually use the mean TAC as the input. You can do this in parallel with #1.
- You'd then run mri_gtmpvc, something like
mri_gtmpvc --i pet.nii.gz --psf PSF --auto-mask PSF+2 .01 --seg gtmseg.mgz --reg reg.lta --default-seg-merge --o gtmpvc.output
PSF is the point-spread FWHM of the scanner; reg.lta is the registration from #2. By default, this will scale by pons. The output will be gtm.stats.dat and gtm.nii.gz. They both basically have the same information. gtm.stats.dat is an easy to read text file. Where each row is an ROI, something like:
9 17 Left-Hippocampus subcort_gm 473 174.083 1.406 0.1216
9 = nineth row 17 = index for RO Left-Hippocampus = name of ROI subcort_gm = tissue class 473 = number of PET voxels in the ROI 174 = variance reduction factor for ROI (based on GLM/SGTM) 1.406 = PVC uptake of ROI relative to Pons 0.1216 = resdiual varaince across voxels in the ROI
gtm.nii.gz is a nifti file with each "voxel" being an ROI. The value is the PVC uptake of ROI relative to Pons. These can easily be concatenated together (mri_concat) and used as input to mri_glmfit for group analysis.
On 01/08/2016 04:22 AM, Benjamin Spurny wrote:
Dear Freesurfer experts!
I am currently working on PET analysis using FS
I coregistered my PET with the processed MR using bbregister, transfered it to a surface using mri_vol2surf and now createt an overlay in freeview with the lh.inflated and used the labels from the lh.aparc.a2009s.annot file.
In freeview i get the corresponding BP value for each vertex now but is there a way to get a list of vertices with the corresponding BP value and the corresponding ROI this vertex belongs to? Or is there a better to do this analyis?
Many thanks in advance!
Benjamin
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