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In Electrical impedance tomography, it was shown that the use of prior information and the Approximation Error Method improves the spatial resolution using the Gauss-Newton method. However, the D-bar method’s approach to solve the inverse problem makes difficult to include statistical priors in the algorithm. In this work a method of correcting the data based on Bayesian techniques to incorporate statistical priors in the D-bar algorithm is proposed. Results are shown on experimental tank data.
This presentation is part of Minisymposium “MS20 - Advances in Reconstruction Methods for Electrical Impedance Tomography (3 parts)”
organized by: Melody Alsaker (Gonzaga University) , Samuli Siltanen (University of Helsinki) .