Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment
Korean Journal of Radiology 2021³â 22±Ç 5È£ p.792 ~ p.800
À̺´´ë(Lee Byoung-Dai) - Kyonggi University Division of Computer Science and Engineering
À̹«¼÷(Lee Mu-Sook) - Keimyung University Dongsan Hospital Department of Radiology
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.
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Bone age assessment, Left hand and wrist radiographs, Artificial intelligence, Convolutional neural network, Deep learning
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À¯È¿¼º°á°ú(Recomendation)
AI-based automated bone age assessments can reduce the burden of radiologists who handle a large number of images to determine bone age. It can also significantly reduce the subjectivity, and inter- and intra-observer variabilities associated with traditional bone age assessment methods.