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    In-vitro Diagnosis of Approximal Caries in Teeth Periapical Radiography with Different Exposure Parameters
    (Pera Yayincilik Hizmetleri, 2023) Altun, Oguzhan; Ozen, Duygu Celik; Dedeoglu, Numan; Duman, Suayip Burak; Eser, Gozde; Topaloglu, Edanur; Ozemre, Begum
    Objective: The aim of this study was to evaluate periapical radiographs of enamel caries, dentin caries, and deep caries with exposed pulp and intact teeth obtained in vitro using photo-stimulated phosphor plates (PSP) under different exposure parameters. Methods: 3 non-carious extracted molars were selected. The obtained molars were embedded in the wax created from pink wax by ensuring approximal contact and a base was created. 14 different imaging protocols were used with 60 kVp, 4 mA 0.02-0.1 second and 70 kVp 7 mA, 0.25-1.25 second exposure parameters. Intact teeth were imaged with these various imaging protocols. Artificial cavities were then created for enamel caries, dentin caries and deep caries with exposed pulp and imaged according to the same protocols. The images were evaluated by 3 clinicians who were blind to the exposure protocol and caries status. Inter-observer agreement with actual situations was examined with Kappa statistics. Results: In the low-dose group, the kappa values of observer 1, observer 2, and observer 3 were 0.905, 0.952, 0.952, respectively. The kappa values of observer 1, observer 2, and observer 3 in the ultralow-dose group were 0.833, 1, 1, and the kappa values of observer 1, observer 2, and observer 3 in the high-dose group were 1, 1, 0.833, respectively. The results obtained in all groups showed a statistically significant-excellent agreement (p<0.001). Conclusion: Approximal caries can be diagnosed with intraoral radiography obtained with low radiation doses with PSP in dentistry. Thus, patients could be exposed to less ionizing radiation.
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    YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition
    (Bmc, 2024) Beser, Busra; Reis, Tugba; Berber, Merve Nur; Topaloglu, Edanur; Gungor, Esra; Kilic, Munevver Coruh; Duman, Sacide
    ObjectivesIn the interpretation of panoramic radiographs (PRs), the identification and numbering of teeth is an important part of the correct diagnosis. This study evaluates the effectiveness of YOLO-v5 in the automatic detection, segmentation, and numbering of deciduous and permanent teeth in mixed dentition pediatric patients based on PRs.MethodsA total of 3854 mixed pediatric patients PRs were labelled for deciduous and permanent teeth using the CranioCatch labeling program. The dataset was divided into three subsets: training (n = 3093, 80% of the total), validation (n = 387, 10% of the total) and test (n = 385, 10% of the total). An artificial intelligence (AI) algorithm using YOLO-v5 models were developed.ResultsThe sensitivity, precision, F-1 score, and mean average precision-0.5 (mAP-0.5) values were 0.99, 0.99, 0.99, and 0.98 respectively, to teeth detection. The sensitivity, precision, F-1 score, and mAP-0.5 values were 0.98, 0.98, 0.98, and 0.98, respectively, to teeth segmentation.ConclusionsYOLO-v5 based models can have the potential to detect and enable the accurate segmentation of deciduous and permanent teeth using PRs of pediatric patients with mixed dentition.