It is hard to say. The 0.25mm may be throwing it off. You can try adding -r
0.25. This will increase the force that repels the pial surface from the white
by a factor of 10. That might be enough. But there are a lot of places where
mris_make_surfaces assumes that the voxels are 1mm. Sometimes
Can you try running the ROI results with mri_glmfit? ie, if you ran
aparcstats2table to get the ROI results you input to SPSS, then run
mri_glmfit --table table.dat --fsgd g1v4.fsgd --C group.diff.mtx --glmdir
table.g1v4.glmdir
where table.dat is the result of aparcstats2table
Then look at
ok, this is very strange to me. Can you send the result of these two commands
pwd
and
ls -l BN_Atlas_subcotex.mgz
On 12/13/2019 2:22 AM, Boris Rauchmann wrote:
External Email - Use Caution
yes to both. I always get the error ERROR: cannot find aseg...
On Fri, Dec 13, 2019 at 12:58
OK. Does that mean there is not a problem? I'm just not sure if you need
anything from us.
On 12/12/2019 7:37 PM, Joshi, Nandita wrote:
External Email - Use Caution
Hi Dr. Greve,
I apologize, maybe I should have been more specific. What I meant to say was,
for example, in the
Hi Monica
hmmm, hard to say without seeing the dataset. You could try using expert
options to change some of the intensity thresholds if this is something
specific to your acquiisition. If you upload the gzipped subject dir we
will take a look
cheers
Bruce
On Fri, 13 Dec 2019, Monica
Hi Sparsh
probably easiest to do with a surface, but I defer to Ruopeng
cheers
Bruce
On Fri, 13 Dec
2019, Sparsh Jain wrote:
External Email - Use Caution
Hi!
Can I create a brain volume with about 40% opacity and save it as a matlab
figure? The volume may not be
very
Hi Ricardo
hmmm, the fact that it says "MRImaskDifferentGeometry" suggests that your
skull stripping didn't end up "conforming", which is probably the error.
Try something like:
cp brainmask.mgz brainmask.bet.mgz
mri_convert -rl orig.mgz brainmask.bet.mgz brainmask.mgz
then rerun and see
External Email - Use Caution
Dear Freesurfer experts,
I’m trying to run recon-all on "T1-like” data (it is actually a quantitative
MRI map with a contrast very similar to T1).
I managed to put it through recon-all’s autorecon1 stage without any major
tricks or modifications
