Automatic detection and segmentation of chorda tympani under microscopic vision in otosclerosis patients via convolutional neural networks.

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI) techniques, especially deep learning (DL) techniques, have shown promising results for various computer vision tasks in the field of surgery. However, AI-guided navigation during microscopic surgery for real-time surgical guidance and decision support is much more complex, and its efficacy has yet to be demonstrated. We propose a model dedicated to the evaluation of DL-based semantic segmentation of chorda tympani (CT) during microscopic surgery.

Authors

  • Yu Huang
    School of Data Science and Software Engineering, Qingdao University, Qingdao 266021, China.
  • Xin Ding
    Department of Otorhinolaryngology Head and Neck Surgery, the Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Yang Zhao
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Xu Tian
    Department of Otorhinolaryngology Head and Neck Surgery, the Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Guodong Feng
    Department of Otorhinolaryngology Head and Neck Surgery, the Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Zhiqiang Gao
    Beijing Entry-Exit Inspection and Quarantine Bureau, Beijing 100026, China.