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In this paper, we propose to extend the notion of global brain age by estimating brain structure ages using structural magnetic resonance imaging. To this end, an ensemble of deep learning models is first used to estimate a 3D aging map (i.e., voxel\u2010wise age estimation). Then, a 3D segmentation mask is used to obtain the final brain structure ages. This biomarker can be used in several situations. First, it enables to accurately estimate the brain age for the purpose of anomaly detection at the population level. In this situation, our approach outperforms several state\u2010of\u2010the\u2010art methods. Second, brain structure ages can be used to compute the deviation from the normal aging process of each brain structure. This feature can be used in a multi\u2010disease classification task for an accurate differential diagnosis at the subject level. Finally, the brain structure age deviations of individuals can be visualized, providing some insights about brain abnormality and helping clinicians in real medical contexts.<\/jats:p>","DOI":"10.1002\/hbm.26558","type":"journal-article","created":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T06:19:04Z","timestamp":1705040344000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":49,"title":["Brain structure ages\u2014A new biomarker for multi\u2010disease classification"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3980-8029","authenticated-orcid":false,"given":"Huy\u2010Dung","family":"Nguyen","sequence":"first","affiliation":[{"name":"Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800  Talence France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Micha\u00ebl","family":"Cl\u00e9ment","sequence":"additional","affiliation":[{"name":"Univ. 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