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Brain morphometry based classification from magnetic resonance (MR) acquisitions has been widely investigated in the diagnosis of Alzheimer's disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). In the literature, a morphometric representation of brain structures is obtained by spatial normalization of each image into a common space (i.e., a pre‐defined atlas) via non‐linear registration, thus the corresponding regions in different brains can be compared. However, representations generated from one single atlas may not be sufficient to reveal the underlying anatomical differences between the groups of disease‐affected patients and normal controls (NC). In this article, we propose a different methodology, namely the multi‐atlas based morphometry, which measures morphometric representations of the same image in different spaces of multiple atlases. Representations generated from …