Name
Title | ||
|---|---|---|
Physiology-based regularization improves noninvasive reconstruction and localization of cardiac electrical activity |
Abstract | ||
|---|---|---|
The objective of the inverse problem of electrocardiography is to noninvasively reconstruct information about electrical activity at the heart surface (epicardium), from electrical measurements on the body surface and a patient-specific torso-heart geometry. This is complicated by the ill-posedness of the inverse problem. Previously, we have shown that a realistic basis can be created from (simulated) epicardial training potentials. Potentials reconstructed with traditional methods can be projected onto this basis, improving the quality of reconstructions. Here, we propose a novel superior method called `physiology-based regularization' that renders traditional reconstruction and projection unnecessary. Instead, reconstruction of epicardial electrograms is achieved directly, by pursuing a sparse representation in terms of this realistic basis. We validate this method by invasive epicardial electrogram recordings in a canine experiment. We further demonstrate that by creating a realistic basis for a specific purpose, this method can answer clinical questions with improved accuracy. Ultimately, physiology-based regularization would improve patient care by yielding patient-specific results, inspired by electrophysiological knowledge and optimized to answer clinically relevant questions. |
Year | Venue | Keywords |
|---|---|---|
2014 | CinC | electrocardiography,inverse problems,medical signal processing,signal reconstruction,canine experiment,cardiac electrical activity localization,epicardial electrograms,epicardium,heart surface,ill posedness,inverse problem,noninvasive reconstruction,patient specific torso-heart geometry,physiology based regularization,sparse representation,surface reconstruction,physiology,electrodes,image reconstruction,electric potential,heart |
Field | DocType | Volume |
Iterative reconstruction,Surface reconstruction,Sparse approximation,Regularization (mathematics),Inverse problem,Patient care,Physiology,Mathematics | Conference | 41 |
ISSN | Citations | PageRank |
2325-8861 | 1 | 0.37 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| matthijs jm cluitmans | 1 | 1 | 0.37 |
| monique mj de jong | 2 | 1 | 0.37 |
| Paul G A Volders | 3 | 8 | 4.86 |
| Ralf L. M. Peeters | 4 | 62 | 22.61 |
| Ronald L. Westra | 5 | 50 | 9.00 |