SD-Net: joint surgical gesture recognition and skill assessment.

Journal: International journal of computer assisted radiology and surgery
Published Date: Oct 16, 2021

Abstract

PURPOSE: Surgical gesture recognition has been an essential task for providing intraoperative context-aware assistance and scheduling clinical resources. However, previous methods present limitations in catching long-range temporal information, and many of them require additional sensors. To address these challenges, we propose a symmetric dilated network, namely SD-Net, to jointly recognize surgical gestures and assess surgical skill levels only using RGB surgical video sequences.

Authors

  • Jinglu Zhang
    National Centre for Computer Animation, Bournemouth University, Bournemouth, UK.
  • Yinyu Nie
    Technical University of Munich, Munich, Germany. yinyu.nie@tum.de.
  • Yao Lyu
    National Centre for Computer Animation, Bournemouth University, Bournemouth, UK.
  • Xiaosong Yang
    National Centre for Computer Animation, Bournemouth University, Bournemouth, UK.
  • Jian Chang
    National Centre for Computer Animation, Bournemouth University, Bournemouth, UK.
  • Jian Jun Zhang
    National Centre for Computer Animation, Bournemouth University, Bournemouth, UK.

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