Artificial Intelligence in Abdominal, Gynecological, Obstetric, Musculoskeletal, Vascular and Interventional Ultrasound.
Authors
Affiliations (16)
Affiliations (16)
- Department of Radiology, Aarhus University Hospital, Denmark.
- 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.
- Emergency Physician Fiona Stanley Hospital, Perth, Australia.
- University of South Carolina School of Medicine, Department of Medicine, Columbia, SC, USA.
- Translational Gastroenterology Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Medical Department B, University Hospital Münster, Münster, Germany.
- School of Dentistry & Medical Sciences, Charles Sturt University, New South Wales, Australia.
- Director of the Ultrasound Division of the Institute of Radiology, Hospital das Clinicas, School of Medicine, University of Sao Paulo, Brazil.
- Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China.
- National Centre for Ultrasound in Gastroenterology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Norway.
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Taipei, Taiwan.
- Department of Ultrasound Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Department of Interventional Ultrasound, Chinese PLA General Hospital, Beijing, China.
- Gastroenterology, Sana Hospital Lichtenberg, Berlin, Germany.
- Center for Surgical Ultrasound, Dep of Surgery, Zealand University Hospital, Køge Institute for Clinical Medicine, University of Copenhagen, Denmark.
- Department of Gastroenterology and Hepatology, Elias Emergency University Hospital, Carol Davila University of Medicine and Pharmacy Bucharest, Romania.
- Department General Internal Medicine (DAIM), Hospitals Hirslanden Bern Beau Site, Salem and Permanence, Bern, Switzerland. Electronic address: [email protected].
Abstract
Artificial Intelligence (AI) is a theoretical framework and systematic development of computational models designed to execute tasks that traditionally require human cognition. In medical imaging, AI is used for various modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, and pathologies across multiple organ systems. However, integrating AI into medical ultrasound presents unique challenges compared to modalities like CT and MRI due to its operator-dependent nature and inherent variability in the image acquisition process. AI application to ultrasound holds the potential to mitigate multiple variabilities, recalibrate interpretative consistency, and uncover diagnostic patterns that may be difficult for humans to detect. Progress has led to significant innovation in medical ultrasound-based AI applications, facilitating their adoption in various clinical settings and for multiple diseases. This manuscript primarily aims to provide a concise yet comprehensive exploration of current and emerging AI applications in medical ultrasound within abdominal, musculoskeletal, and obstetric & gynecological and interventional medical ultrasound. The secondary aim is to discuss present limitations and potential challenges such technological implementations may encounter.