Regularization parameter selection for electrical impedance tomography measurement

Abstract

Electrical impedance tomography (EIT) belongs to a family of electromagnetic imaging modalities, which is a technique used to create image of the electrical properties in the interior of a medium from measurements on its boundary. In principle, measuring both the amplitude and the phase angle of the voltage or current can result in image of the electrical conductivity and permittivity distributions in the interior of the volume. However, the impedance distribution reconstruction in EIT is a nonlinear inverse problem, in which a small amount of noise in the data can lead to enormous errors in the estimates. This ill-posedness problem can be processed with regularization methods. The regularization parameter should be carefully chosen, but it is often heuristically selected in the conventional regularization-based reconstruction algorithms. In this paper, regularization parameter selection for EIT is investigated. Numerical analysis and simulation results are performed to illustrate EIT image reconstruction using different regularization parameters. It is shown that choosing the appropriate regularization parameter plays an important role in EIT image reconstruction.