{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T17:31:39Z","timestamp":1784827899441,"version":"3.55.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T00:00:00Z","timestamp":1710806400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,4,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>The study aims to develop an artificial intelligence (AI) model based on nnU-Net v2 for automatic maxillary sinus (MS) segmentation in cone beam computed tomography (CBCT) volumes and to evaluate the performance of this model.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>In 101 CBCT scans, MS were annotated using the CranioCatch labelling software (Eskisehir, Turkey) The dataset was divided into 3 parts: 80 CBCT scans for training the model, 11 CBCT scans for model validation, and 10 CBCT scans for testing the model. The model training was conducted using the nnU-Net v2 deep learning model with a learning rate of 0.00001 for 1000 epochs. The performance of the model to automatically segment the MS on CBCT scans was assessed by several parameters, including F1-score, accuracy, sensitivity, precision, area under curve (AUC), Dice coefficient (DC), 95% Hausdorff distance (95% HD), and Intersection over Union (IoU) values.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>F1-score, accuracy, sensitivity, precision values were found to be 0.96, 0.99, 0.96, 0.96, respectively for the successful segmentation of maxillary sinus in CBCT images. AUC, DC, 95% HD, IoU values were 0.97, 0.96, 1.19, 0.93, respectively.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Models based on nnU-Net v2 demonstrate the ability to segment the MS autonomously and accurately in CBCT images.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/dmfr\/twae012","type":"journal-article","created":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T22:40:35Z","timestamp":1710888035000},"page":"256-266","source":"Crossref","is-referenced-by-count":34,"title":["Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images"],"prefix":"10.1093","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5036-9867","authenticated-orcid":false,"given":"Ibrahim Sevki","family":"Bayrakdar","sequence":"first","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University , Eskisehir, 26040, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6655-8002","authenticated-orcid":false,"given":"Nermin Sameh","family":"Elfayome","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Cairo University , Cairo, 12613, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8873-5560","authenticated-orcid":false,"given":"Reham Ashraf","family":"Hussien","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Cairo University , Cairo, 12613, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1014-4417","authenticated-orcid":false,"given":"Ibrahim Tevfik","family":"Gulsen","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Alanya Alaaddin Keykubat University , Antalya, 07425, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9677-8690","authenticated-orcid":false,"given":"Alican","family":"Kuran","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Kocaeli University , Kocaeli 41190, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5932-8068","authenticated-orcid":false,"given":"Ihsan","family":"Gunes","sequence":"additional","affiliation":[{"name":"Open and Distance Education Application and Research Center, Eskisehir Technical University , Eskisehir, 26555, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6239-0451","authenticated-orcid":false,"given":"Alwaleed","family":"Al-Badr","sequence":"additional","affiliation":[{"name":"Restorative Dentistry, Riyadh Elm University , Riyadh, 13244, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ozer","family":"Celik","sequence":"additional","affiliation":[{"name":"Department of Mathematics-Computer, Eskisehir Osmangazi University Faculty of Science , Eskisehir, 26040, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaan","family":"Orhan","sequence":"additional","affiliation":[{"name":"Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Ankara University , Ankara, 06560, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,3,19]]},"reference":[{"issue":"8","key":"2024042908001007600_twae012-B1","doi-asserted-by":"crossref","first-page":"20190205","DOI":"10.1259\/dmfr.20190205","article-title":"The maxillary sinus: physiology, development and imaging anatomy","volume":"48","author":"Whyte","year":"2019","journal-title":"Dentomaxillofac Radiol"},{"issue":"5","key":"2024042908001007600_twae012-B2","doi-asserted-by":"crossref","first-page":"903","DOI":"10.1902\/jop.2006.050247","article-title":"Maxillary sinus septa: prevalence, height, location, and morphology. 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