A Bayesian Non-linear Approach for Electrical Impedance Tomography
نویسنده
چکیده
Electrical Impedance Tomography (EIT) of closed conductive media is an ill-posed inverse problem. As regards the corresponding direct problem, the choice of a Finite Elements Method preserves the non linear dependence of the observation set upon the conductivity distribution. In this paper, we show that the Bayesian approach presented in (1) for linear inverse imaging problems is also valid for a non linear problem such as EIT. Our contribution is based on an edge-preserving Markov model as prior for conductivity distribution. Reconstruction results obtained through the optimization of the posterior likelihood criterion yield signii-cant resolution improvement compared to classical methods.
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