This work presents a novel computational technique for unfolding the hippocampus, providing a smooth and consistent mapping from native 3D space to a common coordinate system that is intrinsically defined by hippocampal anatomy. This coordinate system allows for laminar-based sampling of quantitative volumetric data and a means to pool data across subjects without additional registration or warping. We demonstrate the value of this technique with data from a set of healthy young participants scanned at 7T, taking advantage of high-resolution isotropic imaging for visualizing intra-hippocampal features, and employ a single surgical patient case with histology for validation.
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