Influence of regularization in image reconstruction in electrical impedance tomography

Abstract

The purpose of the application of electrical impedance tomography is to obtain images of areas that are difficult to access inside of the chest and other parts of the human being. Today, this has been applied in other areas of engineering with a view to investigate phenomena for which it is difficult to obtain data for robust research. Electrical Impedance Tomography (EIT) of an inverse problem is nonlinear and ill-conditioned. This requires a careful theoretical approach and practice to get good images. To enhance the images, it is important to be sensitive to various parameters that influence the process of image reconstruction, such as the measured voltage and the current density injected into the electrodes. The impedance contact and current density are both high in a point electrode. To reduce this, a large electrode modeled with a Finite Element Method (FEM) is used. A reduced numbers iterations is found when larges electrodes are used. When FEM models are used the performance of the electrical impedance tomography reconstruction algorithm can be improved.