3D Cardiac

3D cardiac reconstruction aims to create comprehensive three-dimensional models of the heart from limited two-dimensional imaging data, such as echocardiograms or magnetic resonance images. Current research focuses on developing advanced deep learning models, including neural radiance fields (NeRFs), diffusion models, and point cloud completion networks, to overcome challenges like sparse data, motion artifacts, and anatomical variability. These advancements enable more accurate and automated assessment of cardiac anatomy and function, improving diagnosis, treatment planning, and the understanding of cardiovascular diseases, particularly myocardial infarction. The resulting 3D models offer improved diagnostic capabilities compared to traditional 2D imaging, leading to more precise and personalized patient care.