Application and Progress of Artificial Intelligence in Fetal Ultrasound

Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However, problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter-observer variability limit the development of traditional ultrasound in clinical applications. The combination of artificial intelligence (AI) and obstetric ultrasound may help optimize fetal ultrasound examination by shortening the examination time, reducing the physician's workload, and improving diagnostic accuracy. AI has been successfully applied to automatic fetal ultrasound standard plane detection, biometric parameter measurement, and disease diagnosis to facilitate conventional imaging approaches. In this review, we attempt to thoroughly review the applications and advantages of AI in prenatal fetal ultrasound and discuss the challenges and promises of this new field.

Automated summary

Prenatal ultrasonography is a crucial tool in pregnancy, but limitations such as fetal mobility, maternal abdominal thickness, and inter-observer variability hinder traditional ultrasound's clinical application. The combination of artificial intelligence (AI) and obstetric ultrasound can optimize fetal ultrasound examination by reducing time, workload, and improving diagnostic accuracy. AI has been successfully used for automatic fetal ultrasound detection, biometric measurements, and disease diagnosis, enhancing traditional imaging approaches. This review comprehensively examines the applications and advantages of AI in prenatal fetal ultrasound, and discusses the challenges and potential of this emerging field.