ResNet-Transformer deep learning model-aided detection of dens evaginatus.

Abstract

Authors

• Siwei Wang
  Department of Thoracic Surgery, The Affiliated Cancer Hospital of Nanjing Medical University & Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing, China.
• Jialing Liu
  State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
• Shihao Li
  Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
• Pengcheng He
  Pediatric Dentistry, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
• Xin Zhou
  School of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, China.
• Zhihe Zhao
  State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases, Department of Orthodontics, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
• Liwei Zheng
  School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, 361024, Fujian Province, China. Electronic address: 2322071053@stu.xmut.edu.cn.

Keywords

External Resources