Thanks Doug,
I'll try that.
Tomer
On Apr 12, 2012, at 2:04 PM, Douglas N Greve wrote:
> First, convert the annotation to a segmentation, something like
>
> mri_annotation2label --subject subjectname --hemi lh --seg lh.aparc.mgh
>
> Then binarize the segmentation and mask with your functiona
First, convert the annotation to a segmentation, something like
mri_annotation2label --subject subjectname --hemi lh --seg lh.aparc.mgh
Then binarize the segmentation and mask with your functional:
mri_binarize --i lh.aparc.mgh --match segid --mask sig.mgh --mask-thresh
2 --o seg.masked.mgh
Th
Hi Doug,
Thanks for the FreeSurferColorLUT.txt link, that solved the anatomical issue.
I am trying to further limit this anatomical mask to voxels that were
significant in the analysis of the functional data (performed on a
surface, e.g. lh).
Thanks,
Tomer
>
> If you want a simple brain mask, yo
If you want a simple brain mask, you can use brainmask.mgz. If you want
to create a mask for a particular anatomical ROI, then you can use
mri_binarize with --match. You can get a list of indicies from
$FREESURFER_HOME/FreeSurferColorLUT.txt. I'm not sure what you are
asking in terms of your s
Hi Bruce,
I seem to be missing something, sorry. How would I define this range?
Also, how can I combine this mask with the functional results (obtained by
running 'selxavg3-sess -s sj -analysis X.lh ...)? What I'll need
eventually is a mask constrained both by anatomical and functional
considerati
Hi Tomer
don't use match - that would be for specific values. Instead specify a
range via:
mri_binarize --min 1 --max 256 --i aparc+aseg.mgz --o aparc+aseg.mask.mgz
cheers
Bruce
On Sat, 7 Apr 2012, to...@nmr.mgh.harvard.edu wrote:
Hi Bruce,
Thanks for the quick response. I got lost with
Hi Bruce,
Thanks for the quick response. I got lost with the mri_binarize step,
could you please explain to me how to find the value for the '--match' for
different structures related to the aparc+aseg.mgz file?
Many thanks,
Tomer
> Hi Tomer
>
> if you binarize the aparc+aseg.mgz with mri_binari
Hi Tomer
if you binarize the aparc+aseg.mgz with mri_binarize that should be pretty
close. Do you need it in the functional geometry? If so, you can use
mri_vol2vol to convert it (with a register.dat created by bbregister)
cheers
Bruce
On Sat, 7 Apr 2012, Tomer Livne wrote:
Hi, I'll appre
Hi, I'll appreciate some help with the following issue.
I need to define an ROI in a whole brain volume to be used as a mask in PyMVPA.
That means having a whole brain .nii file with '1' within the ROI and '0' in
every other voxel.
Is there a way to define a functional ROI in a whole brain volum
