Hi Doug,
After I have the labels then in each subject's T1 space, I will need to
then put them into diffusion and resting state space.
I already have scripts that put the parcellations into subject-specific
diffusion/resting state space (using bbregister, tkregister2, mri_vol2vol
(using the inverse registration from bbregister to put the T1 into
diffusion space), mri_extract_label (extract labels from aparc+aseg.mgz),
and then mri_label2vol (register each of the extracted labels into
diffusion space). Would a similar approach work for the new labels?
Corinna
On Tue, Apr 8, 2014 at 5:42 PM, Douglas N Greve
<gr...@nmr.mgh.harvard.edu>wrote:
>
> Exactly what you have described won't work very well because it would be
> in the volume. I would divide up the parcellations in fsaverage space
> like you've done, then map the parcellation to each subject using
> mri_surf2surf (--sval-annot, see example 6)
>
> doug
>
> On 04/08/2014 04:54 PM, Corinna Bauer wrote:
> > Hello all,
> >
> > I am planning to use mris_divide_parcellation to split the Desikan
> > atlas into smaller ROIs, but will need the new ROIs to be consistent
> > between subjects.
> >
> > Can I achieve this if I register each subject to fsaverage space and
> > then apply the inverse transform to the divided parcellations (which
> > are currently done on the fsaverage brain)?
> >
> > If so, for extracting each label, what would be used for the label
> > number?
> > (i.e. mri_extract_label ${subj_dir}/mri/aparc+aseg.mgz *2035*
> > ${subj_dir}/hardi_labels/ctx-rh-insula.nii)
> >
> >
> > Thanks
> >
> > Corinna
> >
> >
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> --
> Douglas N. Greve, Ph.D.
> MGH-NMR Center
> gr...@nmr.mgh.harvard.edu
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