Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy.

Journal: The Laryngoscope
PMID: 34622964

Abstract

OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based automatic diagnosis system for identifying nasopharyngeal carcinoma (NPC) from noncancer (inflammation and hyperplasia), using both white light imaging (WLI) and narrow-band imaging (NBI) nasopharyngoscopy images.

Authors

  • Jianwei Xu
    School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
  • Xianzhang Bian
    Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
  • Ji-Qing Zhu
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Cheng-Wei Tie
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Xiaoqing Liu
  • Zhiyong Zhou
    Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China.
  • Xiao-Guang Ni
    Department of Endoscopy, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Dahong Qian

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