Development of an artificial intelligence system using deep learning to indicate anatomical landmarks during laparoscopic cholecystectomy.

Journal: Surgical endoscopy
Published Date: Apr 18, 2020

Abstract

BACKGROUND: The occurrence of bile duct injury (BDI) during laparoscopic cholecystectomy (LC) is an important medical issue. Expert surgeons prevent intraoperative BDI by identifying four landmarks. The present study aimed to develop a system that outlines these landmarks on endoscopic images in real time.

Authors

  • Tatsushi Tokuyasu
    Faculty of Information Engineering, Department of Information and Systems Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka-City, Fukuoka, 811-0295, Japan. tokuyasu@fit.ac.jp.
  • Yukio Iwashita
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Yusuke Matsunobu
    Faculty of Information Engineering, Department of Information and Systems Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka-City, Fukuoka, 811-0295, Japan.
  • Toshiya Kamiyama
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Makoto Ishikake
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Seiichiro Sakaguchi
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Kohei Ebe
    Customer Solutions Development, Platform Technology, Olympus Technologies Asia, Olympus Corporation, 2-3 Kuboyama-cho, Hachioji-City, Tokyo, 192-8512, Japan.
  • Kazuhiro Tada
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Yuichi Endo
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Tsuyoshi Etoh
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.
  • Makoto Nakashima
    Faculty of Science and Technology, Division of Computer Science and Intelligent Systems, Oita University, 700 Dannoharu, Oita-City, Oita, 870-1192, Japan.
  • Masafumi Inomata
    Faculty of Medicine, Department of Gastroenterological and Pediatric Surgery, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita, 879-5593, Japan.

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