Ok Eugenio,

I just have a final consideration.

Whenever this last step will be implemented, there will still will be the problem of how to binarize those subfields in a way that makes sense.
Plese correct me if I'm wrong: given that at the end counting all the non-zero voxels will always overestimate the volume calculated with kvlQuantifyPosteriorProbabilityImages, one must further threshold the posteriors to make the two measures consistent with each other. Right?

Best,
Luigi.


in order to make the result consistent with the volume calculated by kvlQuantifyPosteriorProbabilityImages,

2014-09-09 11:58 GMT+02:00 Eugenio Iglesias <e.iglesias@bcbl.eu>:
Hi again, Luigi,

this sentence that you wrote summarizes everything pretty well:
"I think that the posterior files outputted by freesurfer are missing the final step of required to each voxel to the single label with the highest posterior prob."
We will implement this in the next FS release.

Regarding how the discrete labels are computed:
For each voxel, one would look at all the posterior probabilities, and assign the label corresponding to the largest posterior. There is a small chance that there is a tie between 2 (or more) classes; in that case, you can pick between those classes at random.

Cheers,

/Eugenio



Juan Eugenio Iglesias
Postdoctoral researcher BCBL
www.jeiglesias.com
www.bcbl.eu

Legal disclaimer/Aviso legal/Lege-oharra: www.bcbl.eu/legal-disclaimer


----- Original Message -----
From: "Luigi Antelmi" <luigi.antelmi@gmail.com>
To: "e iglesias" <e.iglesias@bcbl.eu>, freesurfer@nmr.mgh.harvard.edu
Sent: Tuesday, September 9, 2014 11:48:10 AM
Subject: Re: [Freesurfer] hippocampal subfields: from posterior to binary masks

Dear Eugenio,

"assign to each voxel the label with the highest posterior probability" implies that each voxel must belong to one and only one label, right?

I've found that this is not the case with the posterior_*.mgz files outputted by freesurfer, where each voxel (especially the ones with the lower prob values) can belong to multiple labels.

The passages I've done to come up at this conclusion was:
1) binarize all the posterior maps
2) summing them up
3) search for values greater than 1
4) if there are values >1, then there are voxels belonging to multiple labels.

I've found voxels belonging to 7 different labels at the same time!

I think that the posterior files outputted by freesurfer are missing the final step of required to each voxel to the single label with the highest posterior prob.

I think that a clarification from the developers is needed here.

Best regards,
Luigi.