Simulation of Postmarket Fine-tuning of a Computer-aided Detection System for Bone Scintigrams and Its Performance analysis-Reference-Cited by-同舟云学术

Simulation of Postmarket Fine-tuning of a Computer-aided Detection System for Bone Scintigrams and Its Performance analysis

Published:2023 Issue:0 Volume:12 Page:51-63
ISSN:2187-5219
Container-title:Advanced Biomedical Engineering
language:en
Short-container-title:ABE

Author:

Shimada Kaho¹,Daisaki Hiromitsu²,Higashiyama Shigeaki³,Kawabe Joji³,Nakaoka Ryusuke⁴,Shimizu Akinobu¹

Affiliation:

1. Institute of Engineering, Tokyo University of Agriculture and Technology

2. Department of Radiological Technology, Gunma Prefectural College of Health Sciences

3. Department of Nuclear Medicine, Graduate School of Medicine, Osaka Metropolitan University

4. Division of Medical Devices, National Institute of Health Sciences

Publisher

Japanese Society for Medical and Biological Engineering

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering,Biomaterials,Biotechnology

Link

https://www.jstage.jst.go.jp/article/abe/12/0/12_12_51/_pdf

Reference23 articles.

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3. 3. Pan SJ, Yang Q: A survey on transfer learning. IEEE Trans Knowledge Data Eng. 22(10), 1345–1359, 2009.

4. 4. Pianykh OS, Langs G, Dewey M, Enzmann DR, Herold CJ, Schoenberg SO, Brink JA: Continuous learning AI in radiology: implementation principles and early applications. Radiology. 297(1), 6–14, 2020.

5. 5. Gibson E, Hu Y, Ghavami N, Ahmed HU, Moore C, Emberton M, Huisman HJ, Barratt DC: Inter-site variability in prostate segmentation accuracy using deep learning. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, pp. 506–514, 2018.

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