Hi Alan,

Typically subfields segmentation requires hi-resolution data (e.g. 0.4 x 0.4 mm in-plane resolution). The thickness of a CA subfield typically range between 0.5-1.00 mm, but 1.5 T data does not achieve sub-millimeter resolutions. Further, subfield segmentation typically requires high-contrast data to discern the internal boundaries formed by the stratum radiatum/stratum lacunosum-moleculare (SLRM). I doubt that images produced on a 1.5 T magnet can achieve the necessary contrast. Last, and please someone correct me if what I say is inaccurate, but doesn't the Van Leemput method use statistical priors to apply label probabilities in reference to a generated hippocampal surface? This would imply that the method assigns label probabilities without reference to a subject's SLRM intensity information. For volumetry, I am somewhat skeptical that a method that only relies on a generated surface  would be sensitive to group x subfield interactions; especially double dissociations in which overall volume/shape of the hippocampus may be similar across groups. That the that was generated from potentially low resolution, low contrast data cannot help the matter. Some may disagree about this though and I'd be interested in hearing what other people think about the matter. In general, I am quite optimistic about automated methods to segment the subfields.