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

被引：37

作者：

Lee, Byoung-Dai ^{[1
]}

Lee, Mu Sook ^{[2
]}

机构：

[1] Kyonggi Univ, Div Comp Sci & Engn, Suwon, South Korea

[2] Keimyung Univ, Dongsan Hosp, Dept Radiol, 1035 Dalgubeol daero, Daegu 42601, South Korea

来源：

KOREAN JOURNAL OF RADIOLOGY | 2021年 / 22卷 / 05期

关键词：

Left hand and wrist radiographs; Artificial intelligence; Convolutional neural network; Deep learning; Bone age assessment; SYSTEM; SEGMENTATION; RADIOLOGY; ACCURACY; HAND; MRI;

D O I：

10.3348/kjr.2020.0941

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

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.

引用

页码：792 / 800

页数：9

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