Artificial Intelligence in Musculoskeletal Imaging: Current Status and Future Directions

被引：104
作者：
Gyftopoulos, Soterios [1 ,2 ]
Lin, Dana [1 ]
Knoll, Florian [1 ]
Doshi, Ankur M. [1 ]
Rodrigues, Tatiane Cantarelli [1 ]
Recht, Michael P. [1 ]
机构：
[1] NYU Langone Hlth, Dept Radiol, 660 First Ave, New York, NY 10016 USA
[2] NYU Langone Hlth, Dept Orthoped Surg, New York, NY 10016 USA
来源：
AMERICAN JOURNAL OF ROENTGENOLOGY | 2019年 / 213卷 / 03期
基金：
美国国家卫生研究院;
关键词：
artificial intelligence; deep learning; fast MRI; machine learning; MRI; musculoskeletal imaging; METAL ARTIFACT REDUCTION; NEURAL-NETWORKS; DEEP; MODEL; MRI; IMAGES;
D O I：
10.2214/AJR.19.21117
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：
OBJECTIVE. The objective of this article is to show how artificial intelligence (AI) has impacted different components of the imaging value chain thus far as well as to describe its potential future uses. CONCLUSION. The use of AI has the potential to greatly enhance every component of the imaging value chain. From assessing the appropriateness of imaging orders to helping predict patients at risk for fracture, AI can increase the value that musculoskeletal imagers provide to their patients and to referring clinicians by improving image quality, patient centricity, imaging efficiency, and diagnostic accuracy.
引用
收藏
页码：506 / 513
页数：8
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