Brain Ultrasound

Brain ultrasound research focuses on improving the accuracy and efficiency of fetal brain imaging for anomaly detection and biometric measurement. Current efforts leverage deep learning, particularly U-Net architectures and diffusion models, to automate tasks like segmentation of brain structures, landmark detection for caliper placement, and anomaly identification from 2D ultrasound images. These advancements aim to standardize measurements, reduce reliance on expert interpretation, and improve prenatal care, particularly in resource-limited settings, by enabling more reliable and accessible fetal brain assessments. The development of robust, device-independent algorithms is a key focus to ensure widespread clinical applicability.