Automated Surgical Instrument Detection from Laparoscopic Gastrectomy Video Images Using an Open Source Convolutional Neural Network Platform.

Journal: Journal of the American College of Surgeons
Published Date: Mar 7, 2020

Abstract

BACKGROUND: The common use of laparoscopic intervention produces impressive amounts of video data that are difficult to review for surgeons wishing to evaluate and improve their skills. Therefore, a need exists for the development of computer-based analysis of laparoscopic video to accelerate surgical training and assessment. We developed a surgical instrument detection system for video recordings of laparoscopic gastrectomy procedures. This system, the use of which might increase the efficiency of the video reviewing process, is based on the open source neural network platform, YOLOv3.

Authors

  • Yuta Yamazaki
    From the Division of Gastrointestinal Surgery, Department of Surgery, Kobe University Graduate School of Medicine, Kobe; Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan.
  • Shingo Kanaji
    Division of Gastrointestinal Surgery, Department of Surgery, Graduate School of Medicine, Kobe University, Kobe, Japan. kanashin@med.kobe-u.ac.jp.
  • Takeru Matsuda
  • Taro Oshikiri
  • Tetsu Nakamura
    Division of Gastrointestinal Surgery, Department of Surgery, Graduate School of Medicine, Kobe University, Kobe, Japan. tetsun@med.kobe-u.ac.jp.
  • Satoshi Suzuki
    Department of Infectious Diseases, Tohoku University Graduate School of Medicine 2-1, Seiryo-machi, Aoba-ku Sendai Miyagi 980-8575 Japan.
  • Yuta Hiasa
  • Yoshito Otake
  • Yoshinobu Sato
    Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma, Nara 630-0192, Japan. Electronic address: yoshi@is.naist.jp.
  • Yoshihiro Kakeji
    Division of Gastrointestinal Surgery, Department of Surgery, Graduate School of Medicine, Kobe University, Kobe, Japan. kakeji@med.kobe-u.ac.jp.

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