A modified differential evolution algorithm for the reconstruction of electrical impedance tomography images

It is a well-known fact that exposure of living tissues to ionizing radiation can result on several health problems, where cancer is probably the most complicated. This issue has been strengthening the efforts of both academy and industry to develop and improve non-invasive methods in the last decades. Electrical Impedance Tomography (EIT) is a non-invasive imaging technique that offers a vast field of possibilities due to its low cost, portability, and safety of handling. However, EIT image reconstruction is an ill-posed problem governed by Poisson's Equation: there are no unique mathematical solution to solve this equation. Herein this work we present an EIT reconstruction method based on the optimization of the relative error of reconstruction using a modified differential evolution algorithm. Our approach was compared with genetic algorithms, classical differential evolution, and other modified differential evolution strategies. Results were quantitatively evaluated with ground-truth images using the relative mean squared error, showing that our results reached considerably low error magnitudes. Qualitative evaluation also indicated that our results were anatomically consistent.