Fetal Brain Imaging: A Composite Neural Network Approach for Keyframe Detection in Ultrasound Videos

This article presents a novel approach to keyframe detection in ultrasound videos, specifically focusing on fetal brain imaging. The proposed model is a composite neural network consisting of a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN). The CNN is used to discover features within individual video frames, while the RNN identifies relationships between consecutive frames within a single video. The proposed model could potentially improve the efficiency and accuracy of fetal brain imaging, thereby aiding in the early detection and treatment of various conditions.