Intracardiac Electrical Imaging Using the 12-Lead ECG: A Machine Learning Approach Using Synthetic Data
Date:
Conference Talk at 49th Computing in Cardiology Conference, Virtual
Conference presentation on intracardiac electrical imaging from 12-lead ECGs using machine learning trained with synthetic data. Because paired recordings of surface ECGs and intracardiac electrical activity are scarce, the approach trains deep neural networks on a dataset of more than 16,000 cardiac electrophysiology simulations to reconstruct activation maps and transmembrane voltages from the standard 12-lead ECG. The simulated dataset was released through the LLNL Open Data Initiative to support further research on non-invasive cardiac imaging.
The full paper, the released simulation dataset, and a related patent are available below: IEEE Xplore · CinC PDF · Dataset · Patent