yep, exactly

On 4/8/14 6:00 PM, Corinna Bauer wrote:

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 <greve@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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