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Artificial intelligence in musculoskeletal ultrasound imaging

Authors
 Shin, YiRang  ;  Yang, Jaemoon  ;  Lee, Young Han  ;  Kim, Sungjun 
Citation
 ULTRASONOGRAPHY, Vol.40(1) : 30-44, 2021-01 
Journal Title
 ULTRASONOGRAPHY 
ISSN
 2288-5919 
Issue Date
2021-01
Keywords
Ultrasonography ; Musculoskeletal system ; Artificial intelligence ; Machine learning ; Deep learning
Abstract
Ultrasonography (US) is noninvasive and offers real-time, low-cost, and portable imaging that facilitates the rapid and dynamic assessment of musculoskeletal components. Significant technological improvements have contributed to the increasing adoption of US for musculoskeletal assessments, as artificial intelligence (AI)-based computer-aided detection and computer-aided diagnosis are being utilized to improve the quality, efficiency, and cost of US imaging. This review provides an overview of classical machine learning techniques and modern deep learning approaches for musculoskeletal US, with a focus on the key categories of detection and diagnosis of musculoskeletal disorders, predictive analysis with classification and regression, and automated image segmentation. Moreover, we outline challenges and a range of opportunities for AI in musculoskeletal US practice.
DOI
10.14366/usg.20080
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Sungjun(김성준) ORCID logo https://orcid.org/0000-0002-7876-7901
Yang, Jae Moon(양재문) ORCID logo https://orcid.org/0000-0001-7365-0395
Lee, Young Han(이영한) ORCID logo https://orcid.org/0000-0002-5602-391X
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/181860
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