@inproceedings{5538e5f63f7f41bd8f65e1592b2cdb31,
title = "Development of a VS ultrasound diagnostic system with image evaluation functions",
abstract = "An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of the physician operating the probe. This is because physicians have to constantly adjust the probe position to obtain a cross-section of the target organ, which is constantly shifting due to patient respiratory motions. Therefore, we developed an ultrasound diagnostic robot that works in cooperation with a visual servo system based on deep learning that will help alleviate the burdens imposed on physicians. Two different image processing methods (BiSeNet V2) were used to detect the target kidney location, as well as to evaluate the appropriateness of the obtained ultrasound images (ResNet 50) in developed system.",
keywords = "Deep learning, Robotic ultrasound, Visual servoing",
author = "Jiayi Zhou and Norihiro Koizumi and Yu Nishiyama and Ryosuke Tsumura and Hiroyuki Tsukihara and Naoki Matsumoto",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 11th IEEE Global Conference on Consumer Electronics, GCCE 2022 ; Conference date: 18-10-2022 Through 21-10-2022",
year = "2022",
doi = "10.1109/GCCE56475.2022.10014225",
language = "English",
series = "GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "699--700",
booktitle = "GCCE 2022 - 2022 IEEE 11th Global Conference on Consumer Electronics",
}