Electrocardiogram Image

Electrocardiogram (ECG) image analysis focuses on extracting clinically relevant information from ECG images, often overcoming challenges posed by image quality variations and the need to convert images into analyzable time-series data. Current research heavily utilizes deep learning, employing convolutional neural networks (CNNs), vision transformers, and generative adversarial networks (GANs) for tasks such as disease detection, lead extraction, and electrode localization. These advancements aim to improve the accuracy and efficiency of cardiovascular disease diagnosis, particularly in resource-limited settings where paper-based ECGs are prevalent, and to facilitate the creation of personalized cardiac models.