Utilizing deep learning for automated detection of oral lesions: A multicenter study.

Journal: Oral oncology
Published Date: Jun 3, 2024

Abstract

OBJECTIVES: We aim to develop a YOLOX-based convolutional neural network model for the precise detection of multiple oral lesions, including OLP, OLK, and OSCC, in patient photos.

Authors

  • Yong-Jin Ye
    Division of Mechanics, Beijing Computational Science Research Center, Building 9, East Zone, No.10 East Xibeiwang Road, Haidian District, Beijing 100193, China.
  • Ying Han
    Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Zhen-Lin Guo
    Division of Mechanics, Beijing Computational Science Research Center, Building 9, East Zone, No.10 East Xibeiwang Road, Haidian District, Beijing 100193, China. Electronic address: zguo@csrc.ac.cn.
  • Ming-Wei Huang
    Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, No.22, Zhongguancun South Avenue, Haidian District, Beijing 100081, China. Electronic address: hmwd97@126.com.

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