UMMS Affiliation

Department of Radiology

Publication Date


Document Type



Artificial Intelligence and Robotics | Radiology


Recent advances in deep-learning technology have brought revolutionary changes to artificial intelligence (AI) research and application across industries, yielding major innovations such as facial recognition and self-driving cars. Medicine is no exception, and radiology, which is based on the interpretation of image data obtained through various methods-and has often been compared with computer vision using pattern analysis-is anticipated to experience a major revolution. Despite expectations for increasing research and development of AI-empowered ultrasonography, the clinical implementation of AI in medical ultrasonography faces unique obstacles. It will be necessary to standardize image acquisition, regulate operator and interpreter qualification and performance, integrate clinical information, and provide performance feedback to maximize benefits for patient care.


deep learning, artificial intelligence, AI, radiology, medical ultrasonography, images

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Copyright © 2021 Korean Society of Ultrasound in Medicine (KSUM). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

DOI of Published Version



Kim YH. Artificial intelligence in medical ultrasonography: driving on an unpaved road. Ultrasonography. 2021 Jul;40(3):313-317. doi: 10.14366/usg.21031. Epub 2021 May 10. PMID: 34053212; PMCID: PMC8217795. Link to article on publisher's site

Journal/Book/Conference Title

Ultrasonography (Seoul, Korea)

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Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License