WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging

Xin Wu Cui; Adrian Goudie; Michael Blaivas; Young Jun Chai; Maria Cristina Chammas; Yi Dong; Jonathon Stewart; Tian-An Jiang; Ping Liang; Chandra M Sehgal; Xing-Long Wu; Peter Ching-Chang Hsieh; Saftoiu Adrian; Christoph F Dietrich

doi:10.1016/j.ultrasmedbio.2024.10.016

WFUMB Commentary Paper on Artificial intelligence in Medical Ultrasound Imaging

Ultrasound Med Biol. 2024 Dec 12:S0301-5629(24)00412-5. doi: 10.1016/j.ultrasmedbio.2024.10.016. Online ahead of print.

Authors

Affiliations

¹ Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan, Hubei, China.
² Department of Emergency, Fiona Stanley Hospital, Perth, Australia.
³ Department of Medicine, University of South Carolina School of Medicine, Columbia, SC, USA.
⁴ Department of Surgery, Seoul National University College of Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Republic of Korea.
⁵ Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
⁶ Department of Ultrasound, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
⁷ School of Medicine, The University of Western Australia, Perth, Western Australia, Australia.
⁸ Department of Ultrasound Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
⁹ Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China.
¹⁰ Ultrasound Research Lab, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
¹¹ School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan, Hubei, China.
¹² Chang Gung Memorial Hospital, Taipei, Taiwan.
¹³ Research Center of Gastroenterology and Hepatology, University of Medicine and Pharmacy of Craiova, Craiova, Romania.
¹⁴ Department General Internal Medicine (DAIM), Hospitals Hirslanden Bern Beau Site, Salem and Permanence, Bern, Switzerland. Electronic address: [email protected].

PMID: 39672681
DOI: 10.1016/j.ultrasmedbio.2024.10.016

Abstract

Artificial intelligence (AI) is defined as the theory and development of computer systems able to perform tasks normally associated with human intelligence. At present, AI has been widely used in a variety of ultrasound tasks, including in point-of-care ultrasound, echocardiography, and various diseases of different organs. However, the characteristics of ultrasound, compared to other imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), poses significant additional challenges to AI. Application of AI can not only reduce variability during ultrasound image acquisition, but can standardize these interpretations and identify patterns that escape the human eye and brain. These advances have enabled greater innovations in ultrasound AI applications that can be applied to a variety of clinical settings and disease states. Therefore, The World Federation of Ultrasound in Medicine and Biology (WFUMB) is addressing the topic with a brief and practical overview of current and potential future AI applications in medical ultrasound, as well as discuss some current limitations and future challenges to AI implementation.

Keywords: Artificial intelligence; Contrast-enhanced ultrasound; Deep learning; Machine learning; Point-of-care ultrasound; Ultrasound.

Publication types

Review