Abstract
To obtain unknown source distribution and magnetic moments of discrete magnetized ferromagnetic elementary volumes in our lung phantom we have chosen neural network inverse model. The simplified task was solved by regression multiple-layer perceptron network taught on data generated by multi-pole discrete forward model of the lungs. Magnetic fields corresponding to numerous possible sources were processed. The results are quite promising though more complex cases and especially in-vivo measurements would require much more measuring nodes over the patient/phantom to get enough data for reasonable inversion.
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