I am currently using the last stable version freesurfer 6.0
I gave TRACULA a try on one subject and it took more that 2.5 days to finish
the steps, with PC specs:
- Processor core i7 4 GHz
- VGA Nvidia GTX 980 with 1500 CUDA cores
- 16 GB RAM
I tried to speed it up (trac-all command) using
Thank you both.
How can I deal with partial volume in this case? Would it be possible to use
the partial volume tool for PET on my MD volumes? Sorry if it is a silly idea.
Best Wishes,Shane
On Friday, August 11, 2017, 6:19:45 PM GMT+1, Yendiki, Anastasia
wrote:
I'll let Doug chime in on that tool.
From: freesurfer-boun...@nmr.mgh.harvard.edu
[freesurfer-boun...@nmr.mgh.harvard.edu] on behalf of Shane Schofield
[shane.schofi...@yahoo.com]
Sent: Saturday, August 12, 2017 6:54 AM
To: Freesurfer support list
Subject: Re:
Hi Mina - The part that takes long is running bedpost. If you run trac-all with
the -jobs flag, it'll write out a text file with command lines that can be run
in parallel.
https://surfer.nmr.mgh.harvard.edu/fswiki//trac-all#Parallelprocessing
I do have long-term plans for not using bedpost, but
Hi Shane
we do have some tools to deal with it like mri_compute_volume_fractions
and mri_compute_volume_intensities, or maybe Doug's PET stuff. At the very
least you should probably regress thickness out.
cheers
Bruce
On Sat, 12 Aug 2017, Shane Schofield
wrote:
Thank you both.
How can
Dear all,
I ran my subjects through recon-all successfully. I am in a need to have
custom intensities for segmentation and parcellation in aparc+aseg. Say, 10
- ventricles, 20 - amygdala, 30 - putamen, ...
I would appreciate advice on how I could achieve that.
Thanks in advance,
Martin
you mean instead of colors? I guess it would be easy enough to do in
matlab. Read in the aseg, use find to find the indices of all the voxels
with a particular label, then replace the label with whatever intensity
you want.
cheers
Bruce
On Sat, 12 Aug 2017, Martin Kavec wrote:
> Dear all,
>
Dear FS experts:
I am writting to ask for help about the computation of global mean
thickness. On the FAQ page, one suggestion is that the global mean thickness is
equal to the (lh.thickness*lh.surfarea + rh.thickness.rh.surfarea) /
(lh.surfarea+rh.surfarea). I am wondering how the