Ultrasonic imaging artificial intelligence diagnostic system utilizes high-frequency sound waves and human structure reflection, refraction and attenuation characteristics, with real-time imaging technology for inspection and diagnosis. It adopts the principle of ultrasonography to obtain imaging information of relevant tissues through the conduction and reflection of sound waves inside the human body. This imaging information can be used to analyze and measure the structure and morphology of the tissue as well as the underlying conditions, such as obstruction, injury, etc., in order to determine the presence of disease changes. The development of AI diagnostic systems for ultrasound imaging has benefited from the research and innovation of a number of companies, including IBM's Watson Health, Google's Calico, Microsoft's biometrics, and domestic companies such as Kangfuzi, Tumar Shamkang, and Carbon Cloud Intelligence. These systems help improve the efficiency and accuracy of medical diagnosis by integrating AI technology to provide more accurate, fast and reliable ultrasound diagnostic results.