Intraoperative navigation system for liver resection based on edge-AI and multimodal AI.

Journal: Surgical endoscopy
Published Date: Aug 7, 2025

Abstract

BACKGROUND: Traditional intraoperative navigation methods show insufficient adaptability in dynamic surgical environments. The rapid development of Artificial Intelligence (AI) presents an opportunity to overcome these limitations, making the construction of real-time, adaptive intraoperative navigation systems a key research goal. This study, based on Edge-AI and multimodal AI technologies, aims to develop and evaluate a foundational system for achieving real-time, offline intraoperative navigation and warnings during minimally invasive liver surgery.

Authors

  • Yudan Ma
    Data-Intelligence Surgical Co., Ltd, Suzhou, China.
  • Yunneng Wei
    School of Information Engineering, Nanning University, Nanning, 530200, China.
  • Bingchu Shi
    School of Information Science and Engineering, Beijing City University, Beijing, 100083, China.
  • Ao Liang
    School of Information Science and Engineering, Beijing City University, Beijing, 100083, China.
  • Weixiao Liang
    School of Electronics and Information, Suzhou University of Science and Technology, Suzhou, 215009, China.
  • Xiao Lin
    China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
  • Yifei Tao
    School of Information Engineering, Nanning University, Nanning, 530200, China.
  • Minghui Chen
    Pharmacy Department of Hanzhong, People's Hospital, Hanzhong, Shaanxi 723000, China.
  • Weitao Man
    Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, 168, Litang Road, Changping District, Beijing, 102218, China. mwta03607@btch.edu.cn.

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