Fully automated method for three-dimensional segmentation and fine classification of mixed dentition in cone-beam computed tomography using deep learning.

Abstract

Authors

• Yupeng Hu
  State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, PR China.
• Chang Liu
  Key Lab of Cell Differentiation and Apoptosis of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
• Wei Liu
  Department of Radiation Oncology, Mayo Clinic, Scottsdale, AZ, United States.
• Yutao Xiong
  State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.
• Wei Zeng
  State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
• Jinlong Chen
  State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Dept. of Traumatic and Plastic Surgery, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China.
• Xiang Li
  Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.
• Jixiang Guo
• Wei Tang
  Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Keywords

External Resources