Dear list members,
as you know, the hippocampal subfields given back by FreeSurfer (posterior_left_CA1.mgz, posterior_left_CA2-3.mgz, etc.) are posterior probability maps in the range [0-255] (i.e. [0-1] with 8 bit of quantization). Although there is a way to calculate the volume ( kvlQuantifyPosteriorProbabilityImages) that operates by summing up all the greyscale values https://github.com/neurodebian/freesurfer/blob/master/GEMS/kvlQuantifyPosteriorProbabilityImages.cxx#L107 (an equivalent method is to integrate the histogram over the range 0-255), to my knowledge there is no freesurfer's routine able to extract a binary mask out of the posterior probability map.
What procedure do you use or suggest?
I think there are two possibilities here.
1) As written in the paper from Van Leeput et al. http://www.ncbi.nlm.nih.gov/pubmed/19405131, I can *"assign each voxel to the label with the highest posterior probability"*. Althought I'm wondering why such a thing, documented in the paper, has not been implemented yet, I do not think this is the right way to do it because this procedure do not make any distinction between low probability voxels and high prob ones.
2) Threshold the subfields such that the volumes of the thresholded mask will equal those calculated by integrating the histogram on the domain 0-255; Formally, find *t* such that:
where *H* is the histogram of the subfield.
I prefer the second option because here low prob values are discarded, and because one can apply the equation to a rigid transformed subfield, thus limiting the partial volume effect of the resampling.
What do you think about?
Luigi.
