{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T17:42:16Z","timestamp":1787506936914,"version":"build-2736575974"},"reference-count":24,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82271039"],"award-info":[{"award-number":["82271039"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["PKUSS-2023CRF004"],"award-info":[{"award-number":["PKUSS-2023CRF004"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L232036"],"award-info":[{"award-number":["L232036"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L242132"],"award-info":[{"award-number":["L242132"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L232100"],"award-info":[{"award-number":["L232100"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2022YFC2405401"],"award-info":[{"award-number":["2022YFC2405401"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Dentistry"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.jdent.2025.106295","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T08:01:22Z","timestamp":1765353682000},"page":"106295","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Multi-view deep learning for mandibular landmark localization"],"prefix":"10.1016","volume":"167","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-1850-1528","authenticated-orcid":false,"given":"Zixiang","family":"Gao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zichong","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9234-5783","authenticated-orcid":false,"given":"Yujia","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aonan","family":"Wen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangling","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yijiao","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jdent.2025.106295_bib0001","first-page":"93","article-title":"A new X-ray technique and its application to orthodontia. The introduction of cephalometric radiography","volume":"51","author":"Broadbent","year":"1981","journal-title":"Angle Orthod."},{"key":"10.1016\/j.jdent.2025.106295_bib0002","doi-asserted-by":"crossref","unstructured":"C.A. Hurst, B.L. Eppley, R.J. Havlik, A.M. Sadove, Surgical cephalometrics: applications and developments, Plastic Reconstruct. Surg. (1963), 120 (2007) 1699\u20131700. doi:10.1097\/01.prs.0000282728.97278.a2.","DOI":"10.1097\/01.prs.0000282728.97278.a2"},{"key":"10.1016\/j.jdent.2025.106295_bib0003","doi-asserted-by":"crossref","first-page":"2451","DOI":"10.3892\/etm.2017.4278","article-title":"Preliminary evaluation of cone beam computed tomography in three-dimensional cephalometry for clinical application","volume":"13","author":"Li","year":"2017","journal-title":"Exp. Ther. Med."},{"key":"10.1016\/j.jdent.2025.106295_bib0004","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1186\/s13036-019-0171-6","article-title":"A 3D cephalometric protocol for the accurate quantification of the craniofacial symmetry and facial growth","volume":"13","author":"Pinheiro","year":"2019","journal-title":"J. Biol. Eng."},{"key":"10.1016\/j.jdent.2025.106295_bib0005","first-page":"33","article-title":"Expert consensus for the treatment algorithm for navigationassisted reconstruction of maxillofacial deformities","volume":"23","author":"Zhang","year":"2020","journal-title":"Chin. J. Dent. Res."},{"key":"10.1016\/j.jdent.2025.106295_bib0006","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1016\/j.ijom.2020.02.015","article-title":"Accuracy and reliability of automatic three-dimensional cephalometric landmarking","volume":"49","author":"Dot","year":"2020","journal-title":"Int. J. Oral. Max Surg."},{"key":"10.1016\/j.jdent.2025.106295_bib0007","doi-asserted-by":"crossref","DOI":"10.1259\/dmfr.20170054","article-title":"Automatic localization of three-dimensional cephalometric landmarks on CBCT images by extracting symmetry features of the skull","volume":"47","author":"Neelapu","year":"2018","journal-title":"Dentomaxillofac. Rad."},{"key":"10.1016\/j.jdent.2025.106295_bib0008","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1186\/1471-2342-14-35","article-title":"3D facial landmarks: inter-operator variability of manual annotation","volume":"14","author":"Fagertun","year":"2014","journal-title":"BMC Med. Imaging"},{"key":"10.1016\/j.jdent.2025.106295_bib0009","doi-asserted-by":"crossref","first-page":"1380","DOI":"10.1177\/00220345221112333","article-title":"Automatic 3-dimensional cephalometric landmarking via deep learning","volume":"101","author":"Dot","year":"2022","journal-title":"J. Dent. Res."},{"key":"10.1016\/j.jdent.2025.106295_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2019.101621","article-title":"Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization","volume":"60","author":"Zhang","year":"2020","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.jdent.2025.106295_bib0011","first-page":"1737","article-title":"A knowledge-based algorithm for automatic detection of cephalometric landmarks on CBCT images","volume":"10","author":"Gupta","year":"2015","journal-title":"Int. J. Comput. Ass. Rad."},{"key":"10.1016\/j.jdent.2025.106295_bib0012","article-title":"A novel approach to craniofacial analysis using automated 3D landmarking of the skull","volume":"14","author":"Wilke","year":"2024","journal-title":"Sci. Rep.-UK"},{"key":"10.1016\/j.jdent.2025.106295_bib0013","doi-asserted-by":"crossref","first-page":"6085","DOI":"10.1038\/s41598-019-42533-y","article-title":"MeshMonk: open-source large-scale intensive 3D phenotyping","volume":"9","author":"White","year":"2019","journal-title":"Sci. Rep.-UK,"},{"key":"10.1016\/j.jdent.2025.106295_bib0014","doi-asserted-by":"crossref","first-page":"1086","DOI":"10.3390\/diagnostics13061086","article-title":"Comparison study of extraction accuracy of 3D facial anatomical landmarks based on non-rigid registration of face template","volume":"13","author":"Wen","year":"2023","journal-title":"Diagnostics"},{"key":"10.1016\/j.jdent.2025.106295_bib0015","first-page":"174","article-title":"Automatic determination of mandibular landmarks based on three-dimensional mandibular average model","volume":"55","author":"Gao","year":"2023","journal-title":"Beijing Da Xue Xue Bao Yi Xue Ban"},{"key":"10.1016\/j.jdent.2025.106295_bib0016","series-title":"COMPUTER VISION - ECCV 2018 WORKSHOPS, PT III, 15th European Conference on Computer Vision (ECCV)","first-page":"470","article-title":"Attaining human-level performance with atlas location autocontext for anatomical landmark detection in 3D CT Data","author":"O'Neil","year":"2019"},{"key":"10.1016\/j.jdent.2025.106295_bib0017","doi-asserted-by":"crossref","first-page":"4338","DOI":"10.1109\/TPAMI.2020.3005434","article-title":"Deep learning for 3D point clouds: a survey","volume":"43","author":"Guo","year":"2021","journal-title":"IEEE T Pattern Anal."},{"key":"10.1016\/j.jdent.2025.106295_bib0018","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1111\/ocr.12642","article-title":"Automatic landmark identification in cone-beam computed tomography","volume":"26","author":"Gillot","year":"2023","journal-title":"Orthod. Craniofac. Res."},{"key":"10.1016\/j.jdent.2025.106295_bib0019","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0275033","article-title":"Automatic multi-anatomical skull structure segmentation of cone-beam computed tomography scans using 3D UNETR","volume":"17","author":"Gillot","year":"2022","journal-title":"PloS One"},{"key":"10.1016\/j.jdent.2025.106295_bib0020","series-title":"CLINICAL IMAGE-BASED PROCEDURES","first-page":"32","article-title":"Automatic landmark identification on IntraOralScans","volume":"2022","author":"Baquero","year":"2023"},{"key":"10.1016\/j.jdent.2025.106295_bib0021","series-title":"2016 IEEE Conference on Computer Vision And Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.jdent.2025.106295_bib0022","series-title":"14th European Conference on Computer Vision (ECCV)","first-page":"483","article-title":"Stacked hourglass networks for human pose estimation","author":"Newell","year":"2016"},{"key":"10.1016\/j.jdent.2025.106295_bib0023","series-title":"IEEE\/CVF International Conference on Computer Vision (ICCV)","first-page":"6970","article-title":"Adaptive wing loss for robust face alignment via heatmap regression","author":"Wang","year":"2019"},{"key":"10.1016\/j.jdent.2025.106295_bib0024","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1093\/ejo\/cjr050","article-title":"Precision of identifying cephalometric landmarks with cone beam computed tomography in vivo","volume":"35","author":"Hassan","year":"2013","journal-title":"Eur. J. Orthodont."}],"container-title":["Journal of Dentistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0300571225007389?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0300571225007389?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T06:20:51Z","timestamp":1784787651000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0300571225007389"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":24,"alternative-id":["S0300571225007389"],"URL":"https:\/\/doi.org\/10.1016\/j.jdent.2025.106295","relation":{},"ISSN":["0300-5712"],"issn-type":[{"value":"0300-5712","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-view deep learning for mandibular landmark localization","name":"articletitle","label":"Article Title"},{"value":"Journal of Dentistry","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jdent.2025.106295","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106295"}}