Greetings,
Considering mris_preproc pipeline, I guess that the concatenated output doesn't provide each subject's resamapled and registered "topological" surface in his native space, rather, it encapsulates the interpolated .curv (scalar) data only in a common template space. But, what is the best approach to have subject-wise topological surfaces which all share the same number of vertices and are anatomically registered (i.e. vertex #s are in correspondence), but each surface is still in its native subject space?
Thanks in advance, Sourena Soheili
You can do this with mri_surf2surf, something like
mri_surf2surf --srcsubject yoursubject --trgsubject fsaverage --hemi lh --sval-xyz white --tval lh.yoursubject.white-in-fsaverage --tval-xyz
The output lh.yoursubject.white-in-fsaverage will have the xyz from the native space but the number of vertices will be that of fsaverage.
doug
On 06/11/2012 09:25 AM, Sourena Soheilinezhad wrote:
Greetings,
Considering mris_preproc pipeline, I guess that the concatenated output doesn't provide each subject's resamapled and registered "topological" surface in his native space, rather, it encapsulates the interpolated .curv (scalar) data only in a common template space. But, what is the best approach to have subject-wise topological surfaces which all share the same number of vertices and are anatomically registered (i.e. vertex #s are in correspondence), but each surface is still in its native subject space?
Thanks in advance, Sourena Soheili
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Douglas N Greve -
Sourena Soheilinezhad