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Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment

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Author(s)
Byoung-Dai LeeMu Sook Lee
Keimyung Author(s)
Lee, Mu Sook
Department
Dept. of Radiology (영상의학)
Journal Title
Korean Journal of Radiology
Issued Date
2021
Volume
22
Issue
5
Keyword
Bone age assessmentLeft hand and wrist radiographsArtificial intelligenceConvolutional neural networkDeep learning
Abstract
Bone age assessments are a complicated and lengthy process, which are prone to inter- and intra-observer variabilities. Despite the great demand for fully automated systems, developing an accurate and robust bone age assessment solution has remained challenging. The rapidly evolving deep learning technology has shown promising results in automated bone age assessment. In this review article, we will provide information regarding the history of automated bone age assessments, discuss the current status, and present a literature review, as well as the future directions of artificial intelligence-based bone age assessments.
Keimyung Author(s)(Kor)
이무숙
Publisher
School of Medicine (의과대학)
Citation
Byoung-Dai Lee and Mu Sook Lee. (2021). Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment. Korean Journal of Radiology, 22(5), 792–800. doi: 10.3348/kjr.2020.0941
Type
Article
ISSN
2005--8330
Source
https://www.kjronline.org/DOIx.php?id=10.3348/kjr.2020.0941
DOI
10.3348/kjr.2020.0941
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/43512
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Radiology (영상의학)
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