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| Assessment of the Object Detection Ability of Interproximal Caries on Primary Teeth in Periapical Radiographs Using Deep Learning Algorithms |
| Hongju Jeon, Seonmi Kim, Namki Choi |
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J Korean Acad Pediatr Dent. 2023;50(3):263-276. Published online August 31, 2023 DOI: https://doi.org/10.5933/JKAPD.2023.50.3.263 |
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Assessment of the Object Detection Ability of Interproximal Caries on Primary Teeth in Periapical Radiographs Using Deep Learning Algorithms THE JOURNAL OF THE KOREAN ACADEMY OF PEDTATRIC DENTISTRY. 2023;50(3):263-276  Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: A systematic review Imaging Science in Dentistry. 2021;51(3):237 Diagnosis of Interproximal Caries Lesions in Bitewing Radiographs Using a Deep Convolutional Neural Network-Based Software Caries Research. 2022;56(5-6):503-511 Detection of Proximal Caries Lesions on Bitewing Radiographs Using Deep Learning Method Caries Research. 2022;56(5-6):455-463 A deep learning approach to automatic detection and profiling of dental caries in bitewing and periapical radiographs Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. 2022;134(3):e71 Drone Object Detection Using Deep Learning Algorithms 2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA). 2021; Reliability of the Nyvad criteria for caries assessment in primary teeth European Journal of Oral Sciences. 2011;119(3):225-231 Deep Learning for Early Dental Caries Detection in Bitewing Radiographs . 2021; A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films Scientific Reports. 2019;9(1): The Automatic Detection of Caries in Third Molars on Panoramic Radiographs Using Deep Learning: A Pilot Study . 2021; |
