A genetic algorithm approach to image reconstruction in electrical impedance tomography

Electrical impedance tomography (EIT) determines the resistivity distribution inside an inhomogeneous object by means of voltage and/or current measurements conducted at the object boundary. A genetic algorithm (GA) approach is proposed for the solution of the EIT inverse problem, in particular for the reconstruction of “static” images. Results of numerical experiments of EIT solved by the GA approach (GA-EIT in the following) are presented and compared to those obtained by other more-established inversion methods, such as the modified Newton-Raphson and the double-constraint method. The GA approach is relatively expensive in terms of computing time and resources, and at present this limits the applicability of GA-EIT to the field of static imaging. However, the continuous and rapid growth of computing resources makes the development of real-time dynamic imaging applications based on GAs conceivable in the near future