Machine learning-driven inverse design of puncture needles with tailored mechanics.

Journal: Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Published Date: Jul 23, 2025

Abstract

BACKGROUND: In minimally invasive surgery, designing puncture needles with customizable structures to achieve personalized puncture performance is a significant challenge. Existing reverse design methods struggle to capture the complex nonlinear behavior of needle-tissue interactions.

Authors

  • Yaozong Huang
    Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, Shanghai, People's Republic of China.
  • Fan Zhang
    Department of Anesthesiology, Bishan Hospital of Chongqing Medical University, Chongqing, China.
  • Fanyang Zhang
    Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, Shanghai, People's Republic of China.
  • Xin Wu
    Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, National Center of Technology Innovation for Synthetic Biology, No. 32, Xiqi Road, Tianjin Airport Economic Park, Tianjin 300308, China. Electronic address: wuxin@tib.cas.cn.
  • Yufei Xinye
    Laboratory of Intelligent Control and Robotics, Shanghai University of Engineering Science, Shanghai, People's Republic of China.

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