A global optimization approach to electrical impedance tomography

The objective of this research is to improve upon existing reconstruction methods for static impedance imaging in electrical impedance tomography (EIT), both in speed and quality. A multigrid (MG) method is implemented to speed up the solution of the forward problem in EIT. Compared with direct solution methods and other iterative algorithms, it is more efficient, especially for large system models. On the other hand, due to the nonlinearity of the underlying problem, all existing methods suffer from local optima. In order to find global or at least near optima, simulated annealing (SA) is used to solve the inverse problem of EIT. Some strategies are also proposed, including the insertion of the forward problem in the annealing process, and the discretization of the configuration space. Simulation experiments show the advantages and feasibility of the proposed method