An Approach for Regularization Parameter Optimization in Electrical Impedance Tomography

To improve the ill-posed property of the inverse problem of electrical impedance tomography (EIT), a novel approach, which is based on the product of the residual norm and the penalty function norm (PRP), is presented to optimize the Tikhonov regularization parameters of EIT. To verify the feasibility and effectiveness of the proposed method, simulations of image reconstruction have been carried out considering different sizes, locations, conductivity distributions and numbers of the target areas as well as the scenario of the data with noise. The encouraging simulation results demonstrate that the proposed optimization approach can identify the relatively optimal regularization parameters quickly and also enhance the quality of the reconstructed images.