Improvement in EIT image reconstruction using genetic algorithm

In electrical impedance tomography (EIT), the internal resistivity distribution of the unknown object is computed using the boundary voltage data induced by different current patterns with various reconstruction algorithms. The paper presents an image reconstruction algorithm based on a genetic algorithm (GA) via a two-step approach for the solution of the EIT inverse problem, in particular for the reconstruction of "static" images. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved compared to that of the modified Newton-Raphson algorithm at the expense of increased computational burden.