We don't currently have that information (ie, tissue type) stored with
the ROI. One thing you can do is to run mri_binarize with the --gm
option on aparc+aseg.mgz This uses some rules to determine what is GM
and creates a mask of GM. You can then feed this into mri_segstats with
--mask, and it should only return ROIs that are in the GM mask.
On 11/7/16 8:10 PM, P Taylor wrote:
Thanks, that's useful for getting the ROI volumes and a list of all
that's been found for a particular data set.
I would still like to have a way to identify a listed region as gray
matter or not so that I can parse the file for only GM regions that
have been returned, particularly as different numbers of ROIs are
typically returned in an aparc+aseg file.
I see in the aseg.stats file that there are volumetric summations for
GM quantities, such as:
# Measure lhCortex, lhCortexVol, Left hemisphere cortical gray matter
volume, 238183.759207, mm^3
# Measure rhCortex, rhCortexVol, Right hemisphere cortical gray matter
volume, 240824.502797, mm^3
# Measure Cortex, CortexVol, Total cortical gray matter volume,
479008.262004, mm^3
....
# Measure SubCortGray, SubCortGrayVol, Subcortical gray matter volume,
57815.000000, mm^3
# Measure TotalGray, TotalGrayVol, Total gray matter volume,
643956.262004, mm^3
Are these calculated by summing individual ROI volumes, so that a list
of all possible GM volumes does already exist somewhere?
Thanks,
pt
On Mon, Nov 7, 2016 at 3:39 PM, Douglas N Greve
<gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>> wrote:
I don't know that we have a complete list in one place of just the
aparc+aseg ROIs, but you can get one by running
mri_segstats --seg aparc+aseg.mgz --ctab-default --sum sum.dat
then look in the sum.dat file
On 11/03/2016 04:32 PM, P Taylor wrote:
> Is there an available list of GM regions within the list of
regions in
> the FreeSurferColorLUT.txt?
>
> (In particular, I am interested in a list of GM regions output in a
> default run of recon-all, which seems to have a maximum regionnumber
> of 2035. But a full list is great, too-- I'm not sure which
might be
> already available or easier to generate.)
>
> I had thought of using the segmentation volumes to help me
> differentiate ROIs. For example, I could get rid of regions that
> overlap with the WM volume, but I think that the segmentation might
> come from a slightly different bit of information than the sum of
> segmented regions. As shown in the attached slice image, if I
> underlay the WM segmentation volume (color = white), and overlay a
> "recon-all" parcellation+segmentation map (color = red for GM on
> right, yellow for GM on left, and green for non-GM) to look for
> overlap, I see that some of the WM seg volume overlaps with GM ROIs
> (overlaps are isolated pink-ish voxels and light yellow voxels; one
> highlighted in cross hairs). I guess this difference occurs because
> the segmentation volume comes from the surfaces themselves?
>
> Anyways, this makes me think that I can't automate finding the
GM, and
> I would rather go from LUT numbers, and hence the above question.
>
> Thanks,
> pt
>
>
>
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