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JACIII Vol.26 No.1 pp. 74-82
doi: 10.20965/jaciii.2022.p0074
(2022)

Paper:

A Development of Robotic Scrub Nurse System – Detection for Surgical Instruments Using Faster Region-Based Convolutional Neural Network –

Akito Nakano and Kouki Nagamune

Graduate School of Engineering, University of Fukui
3-9-1 Bunkyo, Fukui, Fukui 910-8507, Japan

Corresponding author

Received:
August 23, 2021
Accepted:
November 10, 2021
Published:
January 20, 2022
Keywords:
robotic scrub nurse, robotic surgery, faster R-CNN
Abstract
A Development of Robotic Scrub Nurse System – Detection for Surgical Instruments Using Faster Region-Based Convolutional Neural Network –

Detection system for surgical instruments

There is presently a shortage of nurses in Japan, with a further shortage of 3,000–130,000 nurses expected. There is also shortage of scrub nurses. Scrub nurses are nurses who work in the operating room. The main job of scrub nurses is to assist surgeons. Scrub nurses are a high turnover rate, because it is a difficult job. Therefore, system for assisting scrub nurses are needed. The purpose of this study was to develop a robotic scrub nurse. As a first step, a detection system for surgical instruments was developed using the “Faster Region-Based Convolutional Neural Network” (Faster R-CNN). In experiments, computer graphics (CG) model images and 3D-printed model images were evaluated, and the system showed high accuracy. Consequently, the Faster R-CNN system can be considered as suitable for detecting surgical instruments.

Cite this article as:
Akito Nakano and Kouki Nagamune, “A Development of Robotic Scrub Nurse System – Detection for Surgical Instruments Using Faster Region-Based Convolutional Neural Network –,” J. Adv. Comput. Intell. Intell. Inform., Vol.26, No.1, pp. 74-82, 2022.
Data files:
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Last updated on May. 20, 2022