Electrical impedance tomography reconstruction through simulated annealing with multi-stage partially evaluated objective functions

The EIT reconstruction problem can be solved as an optimization problem using Simulated Annealing. Different objective functions have already been used: Euclidian distance between the simulated and observed potentials; total least squares error minimization. The objective function was partially evaluated in both methods. In this paper, a new image reconstruction method that combines the best characteristics from both described methods is proposed. The total reconstruction cost is smaller when compared to each method using one objective function alone. A denser reconstruction mesh is used, and a regularization is adopted by adding a new term similar to the first-order Tikhonov functional. The impact of the regularization in the previous two methods is also analyzed.