口腔疾病防治2024，Vol.32Issue(10)：789-796,8.DOI:10.12016/j.issn.2096-1456.202440248
基于深度学习的曲面体层片颌骨病变辅助诊断技术研究
Research on deep learning assisted diagnosis technology of jaw lesions using panoramic radiographs
摘要
Abstract
Objective To study the effect of deep learning applied to the assisted diagnosis of radiolucent lesions and radiopaque lesions of the jaws in panoramic radiography and to reduce the missed diagnosis,with early screening to assist doctors to improve the diagnostic accuracy.Methods This study was approved by the Ethics Committee of the West China Stomatological Hospital of Sichuan University.The YOLO v8m-p2 neural network model was constructed with 443 panoramic images as a subject to read.The labeled images were divided into 354 training sets,45 verification sets,and 44 test sets,which were used for model training,verification,and testing.Accuracy,recall,F-1 score,G score,and mAP50 were used to evaluate the detection performance of the model.Results 443 panoramic images covered the common benign lesions of the jaw,the number of radiolucent lesions of the jaw was 318,containing dentigerous cyst,odontogenic keratocyst,and ameloblastoma.The number of radiopaque lesions was 145,containing idiopathic osteoscle-rosis,odontoma,cementoma,and cemento-osseous dysplasia;the samples are well representative.The accuracy of the YOLO v8m-p2 neural network model in identifying jaw lesions was 0.887,and the recall,F-1 score,G score,and mAP50 were 0.860,0.873,0.873,and 0.863,respectively.The recall rates of dentigerous cyst,odontogenic keratocyst,and ameloblastoma were 0.833,0.941,and 0.875,respectively.Conclusion YOLO v8m-p2 neural network model has good diagnostic performance in preliminary detection of radiolucent and radiopaque lesions of the jaws in panoramic radiography and multi-classification monitoring of radiolucent lesions of jaws,which can assist doctors to screen jaw dis-eases in panoramic radiography.关键词
颌骨囊肿/颌骨肿瘤/影像诊断/曲面体层片/人工智能/深度学习/目标检测/YOLO v8m/神经网络模型Key words
jaw cysts/jaw neoplasm/diagnostic imaging/panoramic radiography/artificial intelligence/deep learning/object detection/YOLO v8m/neural network model分类
口腔医学引用本文复制引用
高歌,刘畅,曾梦雨,彭俊杰,郭际香,汤炜..基于深度学习的曲面体层片颌骨病变辅助诊断技术研究[J].口腔疾病防治,2024,32(10):789-796,8.基金项目
四川省自然科学基金(2024NSFSC0659) （2024NSFSC0659）
四川大学华西口腔医学院探索与研究项目(RD-01-202304) This study was supported by the grants from Sichuan Science and Technology Program(No.2024NSFSC0659) （RD-01-202304）
Research and Develop Program,West China Hospital of Stomatology Sichuan University(No.RD-01-202304). （No.RD-01-202304）
