EIT Reconstruction of Static Images by a Genetic Algorithm Approach

Abstract: A genetic algorithm (GA) approach is proposed for the reconstruction of static images in electrical impedance tomography (EIT). Genetic algorithms can be demonstrated to possess several advantages over more conventional “gradient‐based” techniques. In particular, they are implicitly parallel and realize a good compromise between “exploration” and “exploitation”, thus being more robust against the problem of false minima. The results of GA‐EIT in numerical experiments are presented, compared to those obtained by other, more established inversion methods, such as the modified Newton‐Raphson method and the double‐constraint method. The GA approach is relatively expensive in terms of computation time and resources, requiring (for example) from several minutes to tens of minutes on a Pentium Pro 200‐based machine for normal‐size EIT problems. This currently limits the applicability of GA‐EIT to the field of static imaging. However, in light of the development trend in the field of computing, an extension to real‐time dynamic imaging applications is not inconceivable in the near future.