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We used a new method we developed for automated hippocampal segmentation, called the auto context model, to analyze brain MRI scans of 400 subjects from the Alzheimer's disease neuroimaging initiative. After training the classifier on 21 hand‐labeled expert segmentations, we created binary maps of the hippocampus for three age‐ and sex‐matched groups: 100 subjects with Alzheimer's disease (AD), 200 with mild cognitive impairment (MCI) and 100 elderly controls (mean age: 75.84; SD: 6.64). Hippocampal traces were converted to parametric surface meshes and a radial atrophy mapping technique was used to compute average surface models and local statistics of atrophy. Surface‐based statistical maps visualized links between regional atrophy and diagnosis (MCI versus controls: P = 0.008; MCI versus AD: P = 0.001), mini‐mental state exam (MMSE) scores, and global and sum‐of‐boxes clinical …