Open AccessAutomated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment
Author(s) -
Byoung Dai Lee,
Mu Sook Lee
Publication year - 2021
Publication title -
korean journal of radiology/korean journal of radiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.08
H-Index - 57
eISSN - 2005-8330
pISSN - 1229-6929
DOI - 10.3348/kjr.2020.0941
Subject(s) - bone age , computer science , quantitative assessment , process (computing) , artificial intelligence , medicine , risk analysis (engineering) , operating system
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.