Image reconstruction based on expectation maximization method for electrical impedance tomography (EIT)

Abstract

Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. The image reconstruction for EIT is an inverse problem, which is both nonlinear and ill-posed. The traditional regularization method cannot avoid producing artefacts in reconstructed images in the presence of oscillatory noise with negative portion. In different imaging between two different conductivity distributions, a conductivity change can be seen relatively non-negative to the medium with lower conductivity through some safeguard techniques. Therefore, the statistical method can be used for this purpose. In this paper, the expectation maximization (EM) method is used to solve the inverse problem for EIT. The mathematical model of EIT is transformed to the non-negatively constrained likelihood minimization problem. The solution is obtained by the gradient projection-reduced Newton (GPRN) iteration method. Simulation and experimental results indicate that the reconstructed images with higher quality can be obtained by the EM method.