Prediction of 3D Cardiovascular hemodynamics before and after coronary artery bypass surgery via deep learning

Abstract

Anzai et al. propose a deep learning approach to estimate the 3D hemodynamics of complex aorta-coronary artery geometry in the context of coronary artery bypass surgery. Their method reduces the calculation time 600-fold, while allowing high resolution and similar accuracy as traditional computational fluid dynamics (CFD) method.