Deep learning-based vessel automatic recognition for laparoscopic right hemicolectomy.

Journal: Surgical endoscopy
Published Date: Jan 1, 2024

Abstract

BACKGROUND: In laparoscopic right hemicolectomy (RHC) for right-sided colon cancer, accurate recognition of the vascular anatomy is required for appropriate lymph node harvesting and safe operative procedures. We aimed to develop a deep learning model that enables the automatic recognition and visualization of major blood vessels in laparoscopic RHC.

Authors

  • Kyoko Ryu
    Surgical Device Innovation, National Cancer Center Hospital East, Chiba, Japan.
  • Daichi Kitaguchi
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa-City, Chiba, 277-8577, Japan.
  • Kei Nakajima
    Surgical Device Innovation.
  • Yuto Ishikawa
    Surgical Device Innovation Office, National Cancer Center Hospital East, Kashiwa, Chiba, Japan.
  • Yuriko Harai
    Surgical Device Innovation.
  • Atsushi Yamada
    Department of Mechanical Systems Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan.
  • Younae Lee
    Surgical Device Innovation.
  • Kazuyuki Hayashi
    Surgical Device Innovation.
  • Norihito Kosugi
    Surgical Device Innovation.
  • Hiro Hasegawa
    Surgical Device Innovation Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
  • Nobuyoshi Takeshita
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa-City, Chiba, 277-8577, Japan. ntakeshi@east.ncc.go.jp.
  • Yusuke Kinugasa
  • Masaaki Ito
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, 277-8577, Japan.

Keywords

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