{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T10:21:15Z","timestamp":1787480475748,"version":"build-2736575974"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T00:00:00Z","timestamp":1787443200000},"content-version":"vor","delay-in-days":60,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Oral Health"],"DOI":"10.1186\/s12903-026-09016-9","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T03:36:16Z","timestamp":1782272176000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of an AI-based segmentation model for mandibular fracture segmentation on CBCT using volumetric and 2D slice-based validation approaches"],"prefix":"10.1186","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4506-9996","authenticated-orcid":false,"given":"Ilg\u0131n","family":"Ar\u0131","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3287-4789","authenticated-orcid":false,"given":"Ersagun","family":"Kara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5850-1591","authenticated-orcid":false,"given":"Arzum","family":"Y\u0131lmaz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0536-042X","authenticated-orcid":false,"given":"Ecem","family":"Usman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1977-4431","authenticated-orcid":false,"given":"Alper","family":"Akta\u015f","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"key":"9016_CR1","doi-asserted-by":"crossref","unstructured":"Mehboob A, Barsoum I, Mehboob H, Ouldyerou A, Al-Rub RKA. Computational modelling and optimization of porous plates for mandibular fracture fixation accounting for bone healing. Mater Design. 2025; 254(14):114060.","DOI":"10.1016\/j.matdes.2025.114060"},{"key":"9016_CR2","doi-asserted-by":"crossref","unstructured":"Sandhu S, Husain AA-H, Mergen V et al. Comparative Evaluation of Photon-Counting Detector CT and Cone-Beam CT in the Assessment of Simulated Mandibular Trauma. J Stomatology Oral Maxillofacial Surg. 2025;127(2):102603.","DOI":"10.1016\/j.jormas.2025.102603"},{"issue":"13","key":"9016_CR3","doi-asserted-by":"publisher","first-page":"1384","DOI":"10.1177\/00220345241256618","volume":"103","author":"N van Nistelrooij","year":"2024","unstructured":"van Nistelrooij N, Schitter S, van Lierop P, et al. Detecting mandible fractures in CBCT scans using a 3-stage neural network. J Dent Res. 2024;103(13):1384\u201391.","journal-title":"J Dent Res"},{"issue":"13","key":"9016_CR4","doi-asserted-by":"publisher","first-page":"1404","DOI":"10.3390\/diagnostics14131404","volume":"14","author":"F Alshomrani","year":"2024","unstructured":"Alshomrani F. Cone-beam computed tomography (CBCT)-based diagnosis of dental bone defects. Diagnostics. 2024;14(13):1404.","journal-title":"Diagnostics"},{"issue":"2","key":"9016_CR5","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.joen.2016.10.007","volume":"43","author":"JM Parker","year":"2017","unstructured":"Parker JM, Mol A, Rivera EM, Tawil PZ. Cone-beam Computed Tomography Uses in Clinical Endodontics: Observer Variability in Detecting Periapical Lesions. J Endod Feb. 2017;43(2):184\u20137. https:\/\/doi.org\/10.1016\/j.joen.2016.10.007.","journal-title":"J Endod Feb"},{"issue":"3","key":"9016_CR6","doi-asserted-by":"publisher","first-page":"232","DOI":"10.5624\/isd.20240038","volume":"54","author":"M Dashti","year":"2024","unstructured":"Dashti M, Ghaedsharaf S, Ghasemi S, et al. Evaluation of deep learning and convolutional neural network algorithms for mandibular fracture detection using radiographic images: A systematic review and meta-analysis. Imaging Sci Dentistry. 2024;54(3):232.","journal-title":"Imaging Sci Dentistry"},{"issue":"1","key":"9016_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12891-025-08842-2","volume":"26","author":"J Ju","year":"2025","unstructured":"Ju J, Qu Z, Qing H, Ding Y, Peng L. Evaluation of Artificial Intelligence-based diagnosis for facial fractures, advantages compared with conventional imaging diagnosis: a systematic review and meta-analysis. BMC Musculoskelet Disord. 2025;26(1):1\u201319.","journal-title":"BMC Musculoskelet Disord"},{"issue":"6","key":"9016_CR8","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1016\/j.oooo.2024.07.010","volume":"138","author":"J Mao","year":"2024","unstructured":"Mao J, Du Y, Xue J, et al. Automated detection and classification of mandibular fractures on multislice spiral computed tomography using modified convolutional neural networks. Oral Surg Oral Med Oral Pathol Oral Radiol. 2024;138(6):803\u201312.","journal-title":"Oral Surg Oral Med Oral Pathol Oral Radiol"},{"issue":"6","key":"9016_CR9","doi-asserted-by":"publisher","first-page":"933","DOI":"10.3390\/diagnostics11060933","volume":"11","author":"D-M Son","year":"2021","unstructured":"Son D-M, Yoon Y-A, Kwon H-J, An C-H, Lee S-H. Automatic detection of mandibular fractures in panoramic radiographs using deep learning. Diagnostics. 2021;11(6):933.","journal-title":"Diagnostics"},{"issue":"11","key":"9016_CR10","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.3390\/life12111711","volume":"12","author":"D-M Son","year":"2022","unstructured":"Son D-M, Yoon Y-A, Kwon H-J, Lee S-H. Combined deep learning techniques for mandibular fracture diagnosis assistance. Life. 2022;12(11):1711.","journal-title":"Life"},{"issue":"6","key":"9016_CR11","doi-asserted-by":"publisher","first-page":"4593","DOI":"10.1007\/s00784-022-04427-8","volume":"26","author":"X Wang","year":"2022","unstructured":"Wang X, Xu Z, Tong Y, et al. Detection and classification of mandibular fracture on CT scan using deep convolutional neural network. Clin Oral Investig. 2022;26(6):4593\u2013601.","journal-title":"Clin Oral Investig"},{"key":"9016_CR12","doi-asserted-by":"publisher","first-page":"108291","DOI":"10.1016\/j.compbiomed.2024.108291","volume":"173","author":"T Zhou","year":"2024","unstructured":"Zhou T, Wang H, Du Y, Liu F, Guo Y, Lu H. M3YOLOv5: Feature enhanced YOLOv5 model for mandibular fracture detection. Comput Biol Med. 2024;173:108291.","journal-title":"Comput Biol Med"},{"issue":"6","key":"9016_CR13","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1093\/dmfr\/twae018","volume":"53","author":"A Yari","year":"2024","unstructured":"Yari A, Fasih P, Hosseini Hooshiar M, Goodarzi A, Fattahi SF. Detection and classification of mandibular fractures in panoramic radiography using artificial intelligence. Dentomaxillofacial Radiol. 2024;53(6):363\u201371. https:\/\/doi.org\/10.1093\/dmfr\/twae018.","journal-title":"Dentomaxillofacial Radiol"},{"key":"9016_CR14","doi-asserted-by":"crossref","unstructured":"Seo H, Lee JI, Park JU, Sung IY. Explainable Deep Learning Framework for Classifying Mandibular Fractures on Panoramic Radiographs. J Craniofac Surg. 2026; 37(1\/2): 116-120.","DOI":"10.1097\/SCS.0000000000011892"},{"key":"9016_CR15","doi-asserted-by":"crossref","unstructured":"Mittal U, Khandnor P, Jaiswal M et al. Classification of mandibular fractures from panoramic radiographs using deep learning. Multimedia Tools Appl. 2025;84.34:1\u201322.","DOI":"10.1007\/s11042-025-20834-x"},{"key":"9016_CR16","doi-asserted-by":"publisher","first-page":"27","DOI":"10.4103\/1735-3327.369629","volume":"20","author":"M Shahnavazi","year":"2023","unstructured":"Shahnavazi M, Mohamadrahimi H. The application of artificial neural networks in the detection of mandibular fractures using panoramic radiography. Dent Res J (Isfahan). 2023;20:27. https:\/\/doi.org\/10.4103\/1735-3327.369629.","journal-title":"Dent Res J (Isfahan)"},{"issue":"11","key":"9016_CR17","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1016\/j.ijom.2022.03.056","volume":"51","author":"K Warin","year":"2022","unstructured":"Warin K, Limprasert W, Suebnukarn S, Inglam S, Jantana P, Vicharueang S. Assessment of deep convolutional neural network models for mandibular fracture detection in panoramic radiographs. Int J Oral Maxillofac Surg Nov. 2022;51(11):1488\u201394. https:\/\/doi.org\/10.1016\/j.ijom.2022.03.056.","journal-title":"Int J Oral Maxillofac Surg Nov"},{"issue":"1","key":"9016_CR18","doi-asserted-by":"publisher","first-page":"19596","DOI":"10.1038\/s41598-022-23445-w","volume":"15","author":"S Vinayahalingam","year":"2022","unstructured":"Vinayahalingam S, van Nistelrooij N, van Ginneken B, et al. Detection of mandibular fractures on panoramic radiographs using deep learning. Sci Rep Nov. 2022;15(1):19596. https:\/\/doi.org\/10.1038\/s41598-022-23445-w.","journal-title":"Sci Rep Nov"},{"issue":"2","key":"9016_CR19","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1055\/s-0037-1601374","volume":"31","author":"BB Pickrell","year":"2017","unstructured":"Pickrell BB, Serebrakian AT, Maricevich RS. Mandible Fractures. Semin Plast Surg May. 2017;31(2):100\u20137. https:\/\/doi.org\/10.1055\/s-0037-1601374.","journal-title":"Semin Plast Surg May"},{"issue":"5","key":"9016_CR20","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1016\/j.cjtee.2024.03.005","volume":"27","author":"E Panneerselvam","year":"2024","unstructured":"Panneerselvam E, Ravikumar C, Rajan TA, Balasubramanian S, Krishnakumar Raja VB. Management of multiple and displaced mandibular fractures in a pediatric patient sans mandibular immobilization, sans open reduction and internal fixation. Chin J Traumatol Sep. 2024;27(5):284\u20137. https:\/\/doi.org\/10.1016\/j.cjtee.2024.03.005.","journal-title":"Chin J Traumatol Sep"},{"issue":"9","key":"9016_CR21","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","volume":"30","author":"A Fedorov","year":"2012","unstructured":"Fedorov A, Beichel R, Kalpathy-Cramer J, et al. 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging. 2012;30(9):1323\u201341.","journal-title":"Magn Reson Imaging"},{"issue":"1","key":"9016_CR22","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1186\/s12903-024-03896-5","volume":"24","author":"S Kurt-Bayrakdar","year":"2024","unstructured":"Kurt-Bayrakdar S, Bayrakdar \u0130\u015e, Yavuz MB, et al. Detection of periodontal bone loss patterns and furcation defects from panoramic radiographs using deep learning algorithm: a retrospective study. BMC Oral Health. 2024;24(1):155.","journal-title":"BMC Oral Health"},{"issue":"4","key":"9016_CR23","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1016\/j.jormas.2020.12.006","volume":"122","author":"K Orhan","year":"2021","unstructured":"Orhan K, Bilgir E, Bayrakdar IS, Ezhov M, Gusarev M, Shumilov E. Evaluation of artificial intelligence for detecting impacted third molars on cone-beam computed tomography scans. J Stomatology Oral Maxillofacial Surg. 2021;122(4):333\u20137.","journal-title":"J Stomatology Oral Maxillofacial Surg"},{"key":"9016_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrai.2025.100030","author":"B Kocak","year":"2025","unstructured":"Kocak B, Klontzas ME, Stanzione A, et al. Evaluation metrics in medical imaging AI: fundamentals, pitfalls, misapplications, and recommendations. Eur J Radiol Artif Intell. 2025. https:\/\/doi.org\/10.1016\/j.ejrai.2025.100030. 09\/01\/ 2025;3:100030.","journal-title":"Eur J Radiol Artif Intell"},{"key":"9016_CR25","doi-asserted-by":"publisher","first-page":"102927","DOI":"10.1016\/j.media.2023.102927","volume":"90","author":"S Ostmeier","year":"2023","unstructured":"Ostmeier S, Axelrod B, Isensee F, et al. USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging. Med Image Anal Dec. 2023;90:102927. https:\/\/doi.org\/10.1016\/j.media.2023.102927.","journal-title":"Med Image Anal Dec"},{"key":"9016_CR26","doi-asserted-by":"crossref","unstructured":"Yan W, Yang Q, Syer T, et al. The impact of using voxel-level segmentation metrics on evaluating multifocal prostate cancer localisation. Springer; 2022. pp. 128\u201338.","DOI":"10.1007\/978-3-031-17721-7_14"},{"issue":"6","key":"9016_CR27","doi-asserted-by":"publisher","first-page":"1252","DOI":"10.1016\/j.joms.2009.03.064","volume":"68","author":"R Sawazaki","year":"2010","unstructured":"Sawazaki R, J\u00fanior SML, Asprino L, Moreira RWF, De Moraes M. Incidence and patterns of mandibular condyle fractures. J Oral Maxillofac Surg. 2010;68(6):1252\u20139.","journal-title":"J Oral Maxillofac Surg"},{"issue":"6","key":"9016_CR28","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1016\/j.bjoms.2020.03.014","volume":"58","author":"A Alyahya","year":"2020","unstructured":"Alyahya A, Ahmed AB, Nusair Y, Ababtain R, Alhussain A, Alshafei A. Mandibular condylar fracture: a systematic review of systematic reviews and a proposed algorithm for management. Br J Oral Maxillofac Surg. 2020;58(6):625\u201331.","journal-title":"Br J Oral Maxillofac Surg"},{"issue":"24","key":"9016_CR29","doi-asserted-by":"publisher","first-page":"3140","DOI":"10.3390\/diagnostics15243140","volume":"15","author":"\u00d6 Uranbey","year":"2025","unstructured":"Uranbey \u00d6, G\u00fclba\u011f E, Ekinci B, et al. When CBCT Looks Borderline and Standard Radiology Is Inconclusive: Should We Plate or Should We Wait? Diagnostics. 2025;15(24):3140.","journal-title":"Diagnostics"},{"issue":"4","key":"9016_CR30","doi-asserted-by":"publisher","first-page":"362","DOI":"10.3390\/diagnostics14040362","volume":"14","author":"M Gontarz","year":"2024","unstructured":"Gontarz M, Bargiel J, G\u0105siorowski K, et al. Air Sign in Misdiagnosed Mandibular Fractures Based on CT and CBCT Evaluation. Diagnostics. 2024;14(4):362.","journal-title":"Diagnostics"},{"issue":"6","key":"9016_CR31","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1093\/dmfr\/twaf031","volume":"54","author":"Y Liu","year":"2025","unstructured":"Liu Y, Wang X, Tu Y, Chen W, Shi F, You M. Automatic detection of mandibular fractures on CT scan using deep learning. Dentomaxillofacial Radiol. 2025;54(6):502\u20139. https:\/\/doi.org\/10.1093\/dmfr\/twaf031.","journal-title":"Dentomaxillofacial Radiol"},{"issue":"4","key":"9016_CR32","doi-asserted-by":"publisher","first-page":"373","DOI":"10.3390\/diagnostics14040373","volume":"14","author":"A Rashid","year":"2024","unstructured":"Rashid A, Feinberg L, Fan K. The application of cone beam computed tomography (CBCT) on the diagnosis and management of maxillofacial trauma. Diagnostics. 2024;14(4):373.","journal-title":"Diagnostics"},{"issue":"7","key":"9016_CR33","doi-asserted-by":"publisher","first-page":"69","DOI":"10.9734\/cjast\/2025\/v44i74574","volume":"44","author":"GB Souza","year":"2025","unstructured":"Souza GB, da Silva Izaguirry M, da Rocha Lazzarotto I, Claus TV. Recent Advances in the Use of Cone Beam Computed Tomography (CBCT) in the Diagnosis and Therapeutic Planning of Oral and Maxillofacial Trauma. Curr J Appl Sci Technol. 2025;44(7):69\u201379.","journal-title":"Curr J Appl Sci Technol"}],"container-title":["BMC Oral Health"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12903-026-09016-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12903-026-09016-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12903-026-09016-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T09:59:32Z","timestamp":1787479172000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12903-026-09016-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,24]]},"references-count":33,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["9016"],"URL":"https:\/\/doi.org\/10.1186\/s12903-026-09016-9","relation":{},"ISSN":["1472-6831"],"issn-type":[{"value":"1472-6831","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,24]]},"assertion":[{"value":"3 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This study was approved by the Ethical Committee of Hacettepe University (Approval No: 2024\/20\u201383). Due to the retrospective nature of the study and the use of anonymized data, the requirement for informed consent was waived. All procedures performed in this study involving human participants were conducted in accordance with the ethical standards of the institutional and\/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"1535"}}