Deep-learning-based semantic segmentation of autonomic nerves from laparoscopic images of colorectal surgery: an experimental pilot study.

Journal: International journal of surgery (London, England)
PMID: 36999784

Abstract

BACKGROUND: The preservation of autonomic nerves is the most important factor in maintaining genitourinary function in colorectal surgery; however, these nerves are not clearly recognisable, and their identification is strongly affected by the surgical ability. Therefore, this study aimed to develop a deep learning model for the semantic segmentation of autonomic nerves during laparoscopic colorectal surgery and to experimentally verify the model through intraoperative use and pathological examination.

Authors

  • Shigehiro Kojima
    Surgical Device Innovation.
  • Daichi Kitaguchi
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa-City, Chiba, 277-8577, Japan.
  • Takahiro Igaki
    Surgical Device Innovation Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, 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.
  • Masaaki Ito
    Department of Colorectal Surgery, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, 277-8577, Japan.

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