An artificial intelligence-based nerve recognition model is useful as surgical support technology and as an educational tool in laparoscopic and robot-assisted rectal cancer surgery.

Journal: Surgical endoscopy
PMID: 39073558

Abstract

BACKGROUND: Artificial intelligence (AI) has the potential to enhance surgical practice by predicting anatomical structures within the surgical field, thereby supporting surgeons' experiences and cognitive skills. Preserving and utilising nerves as critical guiding structures is paramount in rectal cancer surgery. Hence, we developed a deep learning model based on U-Net to automatically segment nerves.

Authors

  • Kazuya Kinoshita
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Tetsuro Maruyama
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan. maruyamaatenza@hotmail.co.jp.
  • Nao Kobayashi
    Anaut Inc., Tokyo, Japan.
  • Shunsuke Imanishi
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Michihiro Maruyama
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Gaku Ohira
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Satoshi Endo
  • Toru Tochigi
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Mayuko Kinoshita
    Department of Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba, Japan.
  • Yudai Fukui
    Department of Gastroenterological Surgery, Toranomon Hospital, Tokyo, Japan.
  • Yuta Kumazu
    Department of Surgery, Yokohama City University, Kanagawa, Japan.
  • Junji Kita
    Department of General Surgery, Kumagaya General Hospital, Saitama, Japan.
  • Hisashi Shinohara
  • Hisahiro Matsubara
    Department of Frontier Surgery, Chiba University Graduate School of Medicine, Chiba, Japan.

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