Image reconstruction by electrical impedance tomography using multi-objective simulated annealing

Electrical Impedance Tomography (EIT) image reconstruction can be approached as an optimization problem, intending to minimize the Euclidean distance between the potential values measured in the cross section of the body and the calculated values, for every pattern of current applied, through modelling the problem by the Finite Elements Method (FEM). This formulation is known to be ill-posed, which increases dependence of the EIT on the reconstruction algorithm, which must have a regularization technique to improve the conditioning of the problem. Therefore, this project proposes the use of a Multi-Objective Optimization algorithm in order to find the set of optimal solutions to the problem, aiming to minimize both the Euclidean distance and a regularization parameter.