Abstract
The D-bar method is a direct (noniterative) reconstruction method for 2-D electrical impedance tomography that solves the full nonlinear inverse conductivity problem. However, the idealized model underlying the method is an obstacle to the computation of absolute images by the D-bar method. In this work, a method of correcting the data based on Bayesian techniques to better fit the idealized assumptions is proposed. Preliminary results are shown on experimental tank data.
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