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- W2320313426 abstract "AbstractThe biomagnetic reconstruction of cardiac currents with a trained neural network was performed. The input-output pairs for training the neural network consisted of the magnetic field profiles above the torso and their timings in the heartbeat. A back-propagating algorithm with momentum and bias was utilized for training. The cardiac magnetic field profiles and magnetocardiograms (MCGs) for training the neural network were computed using a realistic, inhomogeneous, finite element model of the heart and torso. The electrical activity of the heart was modelled with distributed dipole sources. Reconstruction of the sources for unknown magnetic field profiles were performed with the trained neural network. The reconstructed cardiac dipole sources were similar to the true dipoles. This shows the feasibility of the biomagnetic reconstruction of cardiac currents with neural networks and a forward model of the cardiac magnetic fields." @default.
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- W2320313426 date "1997-05-01" @default.
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- W2320313426 title "Reconstruction of Cardiac Currents with Simulated MCGs using a Heart-Torso Model and a Neural Network" @default.
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- W2320313426 doi "https://doi.org/10.1080/02564602.1997.11416669" @default.
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