Research Progress on the Application of AI in Prenatal Diagnosis and Fetal Growth and Development

Abstract

This paper focuses on the application of AI in prenatal diagnosis, including ultrasound, MRI, 3D, and 4D imaging, with the use of technologies such as image segmentation, classification, and feature extraction. AI technologies, employing methods like deep convolutional neural networks (DCNN) and generative adversarial networks (GAN), enhance the accuracy of image measurements and diagnostic efficiency, enabling the automatic identification of fetal anatomical structures and abnormalities. The paper explores in detail the performance and effectiveness of intelligent fetal monitoring systems in pregnancy screening, fetal growth and development assessment, and early detection of complications. Despite the significant clinical value AI demonstrates in medical imaging analysis, challenges remain in areas such as privacy protection and data set imbalance.

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