Fetal Plane

Fetal plane analysis in ultrasound imaging focuses on automatically identifying standard fetal anatomical planes for accurate biometric measurements and health assessments. Current research utilizes deep learning models, including variations of ResNet and other architectures, often incorporating self-supervised learning techniques to address data scarcity and improve model generalizability across diverse imaging settings and populations. This work is crucial for improving the efficiency and accuracy of fetal ultrasound interpretation, particularly in resource-limited settings where access to expert clinicians is often lacking, ultimately aiming to enhance prenatal care and reduce perinatal mortality.