New regularized image reconstruction for electrical impedance tomography

Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed, non-linear inverse problem. A new regularization method based on the spatial filtering theory to reconstruct the impedance distribution in EIT is proposed in this paper. The new regularized reconstruction for EIT is independent on the estimation of impedance distribution, so it achieves a lower implementation complexity than the maximum a posteriori (MAP) regularization method. The regularization level in our new method varies spatially so as to be suited to the correlation character of the object's impedance distribution. The computer simulation results indicate that the regularization method based on the spatial filtering theory performs better than Tikhonov regularization method in solving the ill-posed problem of dynamic EIT.