A Mesh-Refinement Method Based on Artificial Neural Networks for Electrical Impedance Tomography

Abstract

Inverse boundary problem are usually solved with a finite element model, with either limited accuracy or huge computation resources. Using a fine mesh results in a computationally demanding task, but when the region of interest is known, when one can easily locally refine the model, aiming for greater local accuracy. In this paper, a novel approach uses artificial neural network to estimate the location of the region of interest and refine this region before solving the inverse problem. The idea is illustrated by solving the electrical impedance tomography inverse problem. Result shows that the proposed method increases the accuracy without significantly affecting the computation resources necessary to solve the inverse problem.