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[en] Included in the Freesurfer 6.0 release [es] Incluido en la version 6.0 de Freesurfer
[en] This tool generates an automated segmentation of the hippocampal subfields based on a statistical atlas built primarily upon ultra-high resolution (~0.1 mm isotropic) ex vivo MRI data. This new method can take advantage high-resolution, dedicated images when available (typically, but not necessarily, T2 weighted), and solves a number of limitations of the in vivo atlas that was distributed with FreeSurfer 5.1-5.3, namely: (a) The image resolution of the training data used to built the atlas was insufficient for the human labelers to completely distinguish the subfields, forcing them to heavily rely on geometric criteria to trace boundaries, which affected the accuracy of their annotations. On the ex vivo images, several of these boundaries are much better visualized, so the annotations are much more reliable. (b) Related to (a): a problematic consequence of the lack of resolution in the in vivo data was that the manual delineation protocol did not include the “molecular layer”, which corresponds to the stratum radiatum, lacunosum moleculare, hippocampal sulcus and molecular layer of the dentate gyrus, and which is also known as “dark band” due to its hypointense appearance in T2 MRI. The absence of the “molecular layer” in the atlas compromised the ability of the atlas to segment high-resolution in vivo data, since this layer is the key appearance feature describing the internal structure of the hippocampus. The new, ex vivo atlas does include this layer in the model. (c) The delineation protocol of the in vivo atlas was designed for the hippocampal body and did not translate well to the hippocampal head or tail. The new atlas was created with a new, specifically designed labeling protocol. (d) Due to issues (a), (b), and (c), the volumes of the subfield in the in vivo atlas did not agree well with those from histological studies (Simic, et al., 1997, Harding, et al., 1998). The volumes derived from the new atlas agree much better with these studies (see the Neuroimage paper).