Oral mucosal disease recognition based on dynamic self-attention and feature discriminant loss.

Journal: Oral diseases
PMID: 37731172

Abstract

OBJECTIVES: To develop a dynamic self-attention and feature discrimination loss function (DSDF) model for identifying oral mucosal diseases presented to solve the problems of data imbalance, complex image background, and high similarity and difference of visual characteristics among different types of lesion areas.

Authors

  • Fei Xie
    Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou 510060, China.
  • Pengfei Xu
    Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, School of Biotechnology, Jiangnan University, Wuxi, China.
  • Xinyi Xi
    School of Information Science and Technology, Northwest University, Xi'an, China.
  • Xiaokang Gu
    School of Information Science and Technology, Northwest University, Xi'an, China.
  • Panpan Zhang
    School of Information Science and Technology, Northwest University, Xi'an, China.
  • Hexu Wang
    Xi'an Key Laboratory of Human-Machine Integration and Control Technology for Intelligent Rehabilitation, Xijing University, Xi'an, China.
  • Xuemin Shen
    Department of Oral Mucosal Diseases, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Keywords

External Resources

Popular Topics
Recent Journals