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BMRMIA: A Platform for Radiologists to Systematically Learn Automated Medical Image Analysis by Three Dimensional Medical Decision Support System

Yankun Cao1, Lina Xu3, Zhi Liu2, Xiaoyan Xiao4, Mingyu Wang5, Qin Li6, Hongji Xu2, Geng Yang6,*

1 School of Software, Shandong University, Jinan, 250101, China
2 School of Information Science and Engineering, Shandong University, Qingdao, 266237, China
3 School of Computer Science and Technology, Shandong Jianzhu University, Jinan, 250012, China
4 Department of Nephrology, Qilu Hospital of Shandong University, Jinan, 250012, China
5 State Key Laboratory of ASIC & Systems, The School of Microelectronics, Fudan University, Shanghai, 200433, China
6 Shenzhen Institute of Information Technology, Shenzhen, 518172, China

* Corresponding Author: Geng Yang. Email: email

(This article belongs to the Special Issue: Application of Deep Learning in Medical Image Analysis (DL-MIA))

Computer Modeling in Engineering & Sciences 2022, 131(2), 851-863. https://doi.org/10.32604/cmes.2022.018424

Abstract

Contribution: This paper designs a learning and training platform that can systematically help radiologists learn automated medical image analysis technology. The platform can help radiologists master deep learning theories and medical applications such as the three-dimensional medical decision support system, and strengthen the teaching practice of deep learning related courses in hospitals, so as to help doctors better understand deep learning knowledge and improve the efficiency of auxiliary diagnosis. Background: In recent years, deep learning has been widely used in academia, industry, and medicine. An increasing number of companies are starting to recruit a large number of professionals in the field of deep learning. Increasing numbers of colleges and universities also offer courses related to deep learning to help radiologists learn automated medical image analysis techniques. For now, however, there is no practical training platform that can help radiologists learn automated medical image analysis systematically. Application Design: The platform proposes the basic learning, model combat, business application (BMR) concept, including the learning guidance system and the assessment training system, which constitutes a closed-loop learning guidance mode of “learning-assessment-training-learning”. Findings: The survey results show that most of radiologists met their learning expectations by using this platform. The platform can help radiologists master deep learning techniques quickly, comprehensively and firmly.

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APA Style
Cao, Y., Xu, L., Liu, Z., Xiao, X., Wang, M. et al. (2022). BMRMIA: A platform for radiologists to systematically learn automated medical image analysis by three dimensional medical decision support system. Computer Modeling in Engineering & Sciences, 131(2), 851-863. https://doi.org/10.32604/cmes.2022.018424
Vancouver Style
Cao Y, Xu L, Liu Z, Xiao X, Wang M, Li Q, et al. BMRMIA: A platform for radiologists to systematically learn automated medical image analysis by three dimensional medical decision support system. Comput Model Eng Sci. 2022;131(2):851-863 https://doi.org/10.32604/cmes.2022.018424
IEEE Style
Y. Cao et al., "BMRMIA: A Platform for Radiologists to Systematically Learn Automated Medical Image Analysis by Three Dimensional Medical Decision Support System," Comput. Model. Eng. Sci., vol. 131, no. 2, pp. 851-863. 2022. https://doi.org/10.32604/cmes.2022.018424



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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