{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T05:59:46Z","timestamp":1787637586136,"version":"build-2736575974"},"reference-count":55,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T00:00:00Z","timestamp":1720742400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2023A1515010792"],"award-info":[{"award-number":["2023A1515010792"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Human Brain Mapping"],"published-print":{"date-parts":[[2024,7,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Research on the local hippocampal atrophy for early detection of dementia has gained considerable attention. However, accurately quantifying subtle atrophy remains challenging in existing morphological methods due to the lack of consistent biological correspondence with the complex curving regions like the hippocampal head. Thereby, this article presents an innovative axis\u2010referenced morphometric model (ARMM) that follows the anatomical lamellar organization of the hippocampus, which capture its precise and consistent longitudinal curving trajectory. Specifically, we establish an \u201caxis\u2010referenced coordinate system\u201d based on a 7\u2009T ex vivo hippocampal atlas following its entire curving longitudinal axis and orthogonal distributed lamellae. We then align individual hippocampi by deforming this template coordinate system to target spaces using boundary\u2010guided diffeomorphic transformation, while ensuring that the lamellar vectors adhere to the constraint of medial\u2010axis geometry. Finally, we measure local thickness and curvatures based on the coordinate system and boundary surface reconstructed from vector tips. The morphometric accuracy is evaluated by comparing reconstructed surfaces with those directly extracted from 7\u2009T and 3\u2009T MRI hippocampi. The results demonstrate that ARMM achieves the best performance, particularly in the curving head, surpassing the state\u2010of\u2010the\u2010art morphological models. Additionally, morphological measurements from ARMM exhibit higher discriminatory power in distinguishing early Alzheimer's disease from mild cognitive impairment compared to volume\u2010based measurements. Overall, the ARMM offers a precise morphometric assessment of hippocampal morphology on MR images, and sheds light on discovering potential image markers for neurodegeneration associated with hippocampal impairment.<\/jats:p>","DOI":"10.1002\/hbm.26715","type":"journal-article","created":{"date-parts":[[2024,7,12]],"date-time":"2024-07-12T10:10:54Z","timestamp":1720779054000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["<scp>MRI<\/scp>\u2010based axis\u2010referenced morphometric model corresponding to lamellar organization for assessing hippocampal atrophy in dementia"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8516-9777","authenticated-orcid":false,"given":"Na","family":"Gao","sequence":"first","affiliation":[{"name":"Electronic &amp; Information Engineering School Harbin Institute of Technology (Shenzhen)  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenfei","family":"Ye","sequence":"additional","affiliation":[{"name":"International Research Institute for Artificial Intelligence, Harbin Institute of Technology at Shenzhen  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hantao","family":"Chen","sequence":"additional","affiliation":[{"name":"Electronic &amp; Information Engineering School Harbin Institute of Technology (Shenzhen)  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyu","family":"Hao","sequence":"additional","affiliation":[{"name":"Electronic &amp; Information Engineering School Harbin Institute of Technology (Shenzhen)  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8819-6228","authenticated-orcid":false,"given":"Ting","family":"Ma","sequence":"additional","affiliation":[{"name":"Electronic &amp; Information Engineering School Harbin Institute of Technology (Shenzhen)  Shenzhen China"},{"name":"International Research Institute for Artificial Intelligence, Harbin Institute of Technology at Shenzhen  Shenzhen China"},{"name":"Peng Cheng Laboratory  Shenzhen China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,7,12]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1801093115"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4522(89)90424-7"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00234087"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0006-8993(00)02991-7"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/biom12101409"},{"key":"e_1_2_9_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2008.01.010"},{"key":"e_1_2_9_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102789"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/s004010050622"},{"key":"e_1_2_9_10_1","doi-asserted-by":"publisher","DOI":"10.1017\/S1041610297004973"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.36255\/exonpublications.cerebralischemia.2021.hippocampus"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2021.750154"},{"key":"e_1_2_9_13_1","unstructured":"Cignoni P. 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