Applications of Artificial Intelligence in Ultrasound Medicine

With the continuous evolution of various algorithms, such as machine learning (ML) and deep learning (DL), ultrasound (US) medicine has also entered the era of artificial intelligence (AI). With the support of AI technology, the problems of poor repeatability and consistency of ultrasound images, which are brought about by operator experience, different instruments, and individual patient differences, have been improved to some extent. In addition, AI has powerful self-learning, image processing, and generalization capabilities, and AI also excels in automatically recognizing complex patterns and providing quantitative assessment of image features. Accordingly, AI has great potential to assist radiologists in obtaining more accurate and reproducible results. In recent years, AI-aided ultrasound imaging has shown rapid growth in applying different systems, such as thyroid, breast, abdomen, gynaecology and obstetrics, vascular, cardiac, and musculoskeletal systems, and some areas have entered the clinical practice stage. The related AI ecology of production, academia, research, application, and management has gradually formed, forming a good trend of simultaneous development of the whole chain.