Inverse problems are broadly characterized by their use of mathematical models for determining unknown system inputs, sources, parameters and/or states from observed system outputs and responses. One important class of inverse problems are those found in bioelectric field imaging of cardiology and neuroscience. Generalized electrocardiographic (ECG) and electroencephalographic (EEG) imaging, use an inverse solution applied to electric voltages recorded on the body/head surface to estimate 1) the complete distribution of electric voltages throughout the torso/head, and/or 2) the cardiac/neural current source characteristics that produce those distributions. To produce such images requires the construction of large-scale geometric patient models, the solution of field equations for the voltage and current distributions, and regularization to deal with the extremely ill-posed nature of the problem. I will present modeling, simulation, visualization, and software results of large-scale bioelectric field problems in cardiology and neuroscience.
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