Boundary image reconstruction based on the nonmonotonic and self-adaptive trust region method for electrical impedance tomography

Abstract

The trust region (TR) method is an effective algorithm for image reconstruction of electrical impedance tomography (EIT). Aiming at the drawback of the traditional TR method, an improved method named the nonmonotonic and self-adaptive trust region (NSTR) method is proposed in this paper, in which three kinds of modified techniques are shown that help in improving the computational precision and convergence speed of the algorithm. The comparisons with image reconstruction are carried out between the NSTR, Levenberd–Marquardt (LM) and TR methods. Simulation experiment results indicate that for both the LM and TR methods it is difficult to accurately reconstruct concave and multiple boundaries. However the NSTR method cannot only realize accurate reconstruction, but also provide faster convergence speed. A noise simulation test is carried out and results show that the NSTR method also has strong stability in image reconstruction for EIT. This new method presents a feasible and effective way to research on image reconstruction for EIT.