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Semin Musculoskelet Radiol 2020; 24(01): 021-029
DOI: 10.1055/s-0039-3400264
Review Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

The Use of Artificial Intelligence in the Evaluation of Knee Pathology

Elisabeth R. Garwood
1   Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts
,
Ryan Tai
1   Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts
,
Ganesh Joshi
1   Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts
,
George J. Watts V
1   Division of Musculoskeletal Imaging and Intervention, Department of Radiology, University of Massachusetts Memorial Medical Center and University of Massachusetts Medical School, Worcester, Massachusetts
› Author Affiliations
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Publication History

Publication Date:
28 January 2020 (online)

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Abstract

Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature.

Keywords

artificial intelligence - magnetic resonance imaging - deep learning - knee
 

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