Review of regularization techniques in electrocardiographic imaging

Regularization methodologies are an integral part in dealing with ill-posedness of inverse problem in electrocardiograhy, expressed in terms of potential distribution on the epicardium. In order to systematically evaluate various regularization techniques under controlled conditions, we employed progressively more complex idealized source models (from single dipole to triplet of dipoles) to calculate body surface potentials, which served as an input data to the inverse problem. In total, we examined, 13 different regularization techniques and found that non-quadratic methods (total variation algorithms) and first-order and second-order Tikhonov regularizations outperformed other methodologies.