Reducing negative effects of quadratic norm regularization on image reconstruction in electrical impedance tomography

Employing the conventional quadratic norm to regularize the inverse problem in electrical impedance tomography often stabilizes the solution at the expense of imposing some smoothness on the reconstructed image. This study proposes a novel multi-regularized approach in order for quadratic norm regularization to reduce its deleterious effects on the reconstructed image. The amounts of regularization exerted on the finite elements over the mesh are not kept constant, but are changed depending on either the sensitivity of the boundary measurements to the finite elements, or the anomaly positioning. The results show that the proposed schemes appreciably improve the image with regard to spatial resolution, artifact, and shape preservation. These schemes considerably reduce the unappealing sensitivity of the inverse solution to the regularization parameter changes as well.