Walther H. W. Schulze

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A framework for step-by-step personalization of a computational model of human atria is presented. Beginning with anatomical modeling based on CT or MRI data, next fiber structure is superimposed using a rule-based method. If available, late-enhancement-MRI images can be considered in order to mark fibrotic tissue. A first estimate of individual(More)
Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the(More)
The goal of ECG-imaging (ECGI) is to reconstruct heart electrical activity from body surface potential maps. The problem is ill-posed, which means that it is extremely sensitive to measurement and modeling errors. The most commonly used method to tackle this obstacle is Tikhonov regularization, which consists in converting the original problem into a(More)
The early detection of myocardial ischemia is an essential lever for its successful treatment. We investigated an ECG monitoring system with 3 electrodes. Optimal electrode positions are determined using a cellular automaton. The spatially heterogeneous effects of myocardial ischemia were modeled by altering 4 electrophysiological parameters: action(More)
In this paper we propose an iteratively regularized Gauss-Newton method to solve the inverse ECG problem and efficiently choose the parameter of regularization. The classical stopping criterium for this regularization technique - Morozov discrepancy principle, cannot be used in our application because the noise level estimate and problem model error are(More)
The problem of non-invasively finding cardiac electrical sources from body surface potential maps (BSPM) is ill-posed. A standard Tikhonov regularization approach to the problem produces a solution biased toward the electrodes and thus to the left ventricular epicardium, which limits its potential to reconstruct endocardial sources. In this work we consider(More)
Electrocardiographic imaging (ECG imaging) is a method to depict electrophysiological processes in the heart. It is an emerging technology with the potential of making the therapy of cardiac arrhythmia less invasive, less expensive, and more precise. A major challenge for integrating the method into clinical workflow is the seamless and correct(More)