3D Cardiac MRI

3D cardiac MRI analysis is rapidly advancing, driven by the need for accurate and efficient methods to diagnose and monitor cardiovascular diseases. Current research focuses on developing deep learning models, including convolutional neural networks and diffusion models, to automate tasks such as segmentation, flow field estimation, and disease detection (e.g., mitral regurgitation). These models are often trained on synthetic data to address the limitations of small and privacy-sensitive real-world datasets, improving both efficiency and the potential for broader clinical application. The ultimate goal is to improve diagnostic accuracy, reduce manual workload, and enable faster, more accessible cardiovascular care.