Hybrid Neural State-Space Modeling for Supervised and Unsupervised Electrocardiographic Imaging
State-space modeling (SSM) provides a general framework for many image reconstruction
tasks. Error in a priori physiological knowledge of the imaging physics, can bring …
tasks. Error in a priori physiological knowledge of the imaging physics, can bring …
Solving the inverse problem of electrocardiography on the endocardium using a single layer source
A Kalinin, D Potyagaylo, V Kalinin - Frontiers in physiology, 2019 - frontiersin.org
The inverse problem of electrocardiography consists in reconstructing cardiac electrical
activity from given body surface electrocardiographic measurements. Despite tremendous …
activity from given body surface electrocardiographic measurements. Despite tremendous …
Improving generalization by learning geometry-dependent and physics-based reconstruction of image sequences
Deep neural networks have shown promise in image reconstruction tasks, although often on
the premise of large amounts of training data. In this paper, we present a new approach to …
the premise of large amounts of training data. In this paper, we present a new approach to …
Frequency-Enhanced Geometric-Constrained Reconstruction for Localizing Myocardial Infarction in 12-Lead Electrocardiograms
Determining the location of myocardial infarction is crucial for clinical management and
therapeutic stratagem. However, existing diagnostic tools either sacrifice ease of use or are …
therapeutic stratagem. However, existing diagnostic tools either sacrifice ease of use or are …
Evaluation of multivariate adaptive non-parametric reduced-order model for solving the inverse electrocardiography problem: A simulation study
In the inverse electrocardiography (ECG) problem, the goal is to reconstruct the heart's
electrical activity from multichannel body surface potentials and a mathematical model of the …
electrical activity from multichannel body surface potentials and a mathematical model of the …
Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Survey
Cardiac digital twins are personalized virtual representations used to understand complex
heart mechanisms. Solving the ECG inverse problem is crucial for accurate virtual heart …
heart mechanisms. Solving the ECG inverse problem is crucial for accurate virtual heart …
Comparison of dipole-based and potential-based ECGI methods for premature ventricular contraction beat localization with clinical data
Introduction: Localization of premature ventricular contraction (PVC) origin to guide the
radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non …
radiofrequency ablation (RFA) procedure is one of the prominent clinical goals of non …
Influence of modeling errors on the initial estimate for nonlinear myocardial activation times imaging calculated with fastest route algorithm
Noninvasive reconstruction of cardiac electrical activity has a great potential to support
clinical decision making, planning, and treatment. Recently, significant progress has been …
clinical decision making, planning, and treatment. Recently, significant progress has been …
Examining the impact of prior models in transmural electrophysiological imaging: A hierarchical multiple-model bayesian approach
Noninvasive cardiac electrophysiological (EP) imaging aims to mathematically reconstruct
the spatiotemporal dynamics of cardiac sources from body-surface electrocardiographic …
the spatiotemporal dynamics of cardiac sources from body-surface electrocardiographic …
Noninvasive reconstruction of transmural transmembrane potential with simultaneous estimation of prior model error
To reconstruct electrical activity in the heart from body-surface electrocardiograms (ECGs) is
an ill-posed inverse problem. Electrophysiological models have been found effective in …
an ill-posed inverse problem. Electrophysiological models have been found effective in …