Frequency-domain Based Optimization of Voxel Networks for Non-invasive Magneto-anatomical Mapping

Abstract Cardiac arrhythmias are one of the world’s leading causes of death. Non-invasive magneto-anatomical mapping aims to identify arrhythmogenic regions based on external magnetic sensors. An alternating two-stage state estimation and parameter optimization scheme has proven promising for cardiac current density estimation. Here, we present a novel approach in simulation working in the frequency domain with the goal to enable convergence in larger voxel structures and increase spatial resolution to move towards clinical relevance.