Dual-task meta-auxiliary learning in laparoscopic cholecystectomy.

Journal: International journal of computer assisted radiology and surgery
Published Date: Jun 26, 2025

Abstract

PURPOSE: Artificial intelligence is transforming surgical practices by improving procedural quality and decision-making. Machine learning-based video analysis can reliably identify surgical milestones, enhancing contextual understanding for surgeons. This study proposes a novel framework for detecting critical view of safety (CVS) in robot-assisted laparoscopic cholecystectomy (RLC) to improve procedural safety.

Authors

  • Rui Guo
    College of Chemistry&Chemical Engineering, Xiamen University, Xiamen 361005, China.
  • Conor Perreault
    Digital Solutions, Intuitive Surgical, Peachtree Corners, GA, 30092, USA.
  • Benjamin Mueller
    Digital Solutions, Intuitive Surgical, Peachtree Corners, GA, 30092, USA.
  • Xi Liu
    Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions, Suzhou Medical College, Soochow University, Suzhou, Jiangsu 215123, China.
  • Anthony Jarc
    3 Medical Research, Intuitive Surgical, Inc. , Norcross, Georgia .

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