View Classification

Echocardiographic view classification aims to automatically identify standard views of the heart in ultrasound images, facilitating efficient and accurate diagnosis. Current research focuses on improving robustness and accuracy using various deep learning architectures, including convolutional neural networks and transformers, often incorporating techniques like multi-view analysis, class-incremental learning, and prompt engineering to handle data variability and scarcity. These advancements are crucial for improving the efficiency and consistency of echocardiographic analysis, potentially reducing diagnostic errors and improving patient care.