{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T18:28:15Z","timestamp":1792607295852,"version":"4.5.0"},"reference-count":27,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T00:00:00Z","timestamp":1735776000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Orthod Craniofacial Res"],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>To assess the accuracy of three commercially available and one open\u2010source deep learning (DL) solutions for automatic tooth segmentation in cone beam computed tomography (CBCT) images of patients with multiple dental impactions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and Methods<\/jats:title><jats:p>Twenty patients (20 CBCT scans) were selected from a retrospective cohort of individuals with multiple dental impactions. For each CBCT scan, one reference segmentation and four DL segmentations of the maxillary and mandibular teeth were obtained. Reference segmentations were generated by experts using a semi\u2010automatic process. DL segmentations were automatically generated according to the manufacturer's instructions. Quantitative and qualitative evaluations of each DL segmentation were performed by comparing it with expert\u2010generated segmentation. The quantitative metrics used were Dice similarity coefficient (DSC) and the normalized surface distance (NSD).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The patients had an average of 12 retained teeth, with 12 of them diagnosed with a rare disease. DSC values ranged from 88.5%\u2009\u00b1\u20093.2% to 95.6%\u2009\u00b1\u20091.2%, and NSD values ranged from 95.3%\u2009\u00b1\u20092.7% to 97.4%\u2009\u00b1\u20096.5%. The number of completely unsegmented teeth ranged from 1 (0.1%) to 41 (6.0%). Two solutions (Diagnocat and DentalSegmentator) outperformed the others across all tested parameters.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>All the tested methods showed a mean NSD of approximately 95%, proving their overall efficiency for tooth segmentation. The accuracy of the methods varied among the four tested solutions owing to the presence of impacted teeth in our CBCT scans. DL solutions are evolving rapidly, and their future performance cannot be predicted based on our results.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ocr.12890","type":"journal-article","created":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T10:38:46Z","timestamp":1735814326000},"page":"433-440","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Automated Cone Beam Computed Tomography Segmentation of Multiple Impacted Teeth With or Without Association to Rare Diseases: Evaluation of Four Deep Learning\u2010Based Methods"],"prefix":"10.1111","volume":"28","author":[{"given":"Eloi","family":"Sinard","sequence":"first","affiliation":[{"name":"UFR Odontologie Universit\u00e9 Paris Cit\u00e9  Paris France"},{"name":"Service de Medecine Bucco\u2010Dentaire AP\u2010HP, Hopital Pitie Salpetriere  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurent","family":"Gajny","sequence":"additional","affiliation":[{"name":"Institut de Biomecanique Humaine Georges Charpak Arts et Metiers Institute of Technology  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muriel","family":"de La Dure\u2010Molla","sequence":"additional","affiliation":[{"name":"UFR Odontologie Universit\u00e9 Paris Cit\u00e9  Paris France"},{"name":"Reference Center for Oral and Dental Rare Disease, ORARES AP\u2010HP, Rothschild Hospital  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0663-6272","authenticated-orcid":false,"given":"Rufino","family":"Felizardo","sequence":"additional","affiliation":[{"name":"UFR Odontologie Universit\u00e9 Paris Cit\u00e9  Paris France"},{"name":"Reference Center for Oral and Dental Rare Disease, ORARES AP\u2010HP, Rothschild Hospital  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2014-2623","authenticated-orcid":false,"given":"Gauthier","family":"Dot","sequence":"additional","affiliation":[{"name":"UFR Odontologie Universit\u00e9 Paris Cit\u00e9  Paris France"},{"name":"Service de Medecine Bucco\u2010Dentaire AP\u2010HP, Hopital Pitie Salpetriere  Paris France"},{"name":"Institut de Biomecanique Humaine Georges Charpak Arts et Metiers Institute of Technology  Paris France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,1,2]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr.20140282"},{"key":"e_1_2_12_3_1","volume-title":"Cone Beam CT for Dental and Maxillofacial Radiology\u2009:Evidence Based Guidelines","author":"Directorate\u2010General for Energy (European Commission)","year":"2012"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr\/74941012"},{"key":"e_1_2_12_5_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr.20140238"},{"key":"e_1_2_12_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40510\u2010022\u201000410\u2010x"},{"key":"e_1_2_12_7_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40510\u2010022\u201000413\u20108"},{"key":"e_1_2_12_8_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph18126201"},{"key":"e_1_2_12_9_1","doi-asserted-by":"publisher","DOI":"10.1259\/dmfr.20140224"},{"key":"e_1_2_12_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0275033"},{"key":"e_1_2_12_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00784\u2010023\u201005048\u20105"},{"key":"e_1_2_12_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010021\u201094093\u20109"},{"key":"e_1_2_12_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joen.2020.12.020"},{"key":"e_1_2_12_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00330\u2010021\u201008455\u2010y"},{"key":"e_1_2_12_15_1","doi-asserted-by":"publisher","DOI":"10.1093\/ejo\/cjac047"},{"key":"e_1_2_12_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdent.2021.103610"},{"key":"e_1_2_12_17_1","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.230024"},{"key":"e_1_2_12_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdent.2022.104238"},{"key":"e_1_2_12_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdent.2024.105130"},{"key":"e_1_2_12_20_1","unstructured":"G.Dot T.Schouman G.Dubois P.Rouch andL.Gajny \u201cPretrained Model for Segmentation of Craniomaxillofacial CT Scans With nnU\u2010Net \u201d2023 https:\/\/doi.org\/10.5281\/zenodo.7548785."},{"key":"e_1_2_12_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2012.05.001"},{"key":"e_1_2_12_22_1","doi-asserted-by":"publisher","DOI":"10.2196\/26151"},{"key":"e_1_2_12_23_1","unstructured":"BibSonomy \u201cR: A Language and Environment for Statistical Computing \u201daccessed January 18 2024 https:\/\/www.bibsonomy.org\/bibtex\/7469ffee3b07f9167cf47e7555041ee7."},{"key":"e_1_2_12_24_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010023\u201049613\u20100"},{"key":"e_1_2_12_25_1","unstructured":"A.Zakirov M.Ezhov M.Gusarev V.Alexandrovsky andE.Shumilov \u201cEnd\u2010To\u2010End Dental Pathology Detection in 3D Cone\u2010Beam Computed Tomography Images \u201daccessed February 2 2024 https:\/\/openreview.net\/forum?id=H1NHbZ3jM."},{"key":"e_1_2_12_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jdent.2021.103865"},{"key":"e_1_2_12_27_1","doi-asserted-by":"publisher","DOI":"10.1155\/2023\/5933003"},{"key":"e_1_2_12_28_1","doi-asserted-by":"publisher","DOI":"10.3390\/children10040708"}],"container-title":["Orthodontics &amp; Craniofacial Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/ocr.12890","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,21]],"date-time":"2025-06-21T09:33:47Z","timestamp":1750498427000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/ocr.12890"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,2]]},"references-count":27,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["10.1111\/ocr.12890"],"URL":"https:\/\/doi.org\/10.1111\/ocr.12890","archive":["Portico"],"relation":{},"ISSN":["1601-6335","1601-6343"],"issn-type":[{"value":"1601-6335","type":"print"},{"value":"1601-6343","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,2]]},"assertion":[{"value":"2024-06-04","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-16","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-01-02","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}