Generation of Synthetic Echocardiograms Using Video Diffusion Models

An echocardiogram is a video sequence of a human heart captured using ultrasound imaging, which helps in diagnosis of cardiovascular diseases. Deep learning methods, which require large amounts of training data, have shown success in using echocardiograms to detect cardiovascular disorders. Large datasets of echocardiograms that can be used for machine learning training are scarce. This problem can be addressed by generating synthetic echocardiograms that can be used for machine learning training. In this paper, we propose a video diffusion method for echocardiograms generation. We show that our method generates better echocardiograms with higher resolution as compared to existing methods.