We prove a new global stability estimate for the Gel’fand–Calderón inverse problem on a two-dimensional bounded domain. Specifically, the inverse boundary value problem for the equation ${- }\Delta \psi + v\hspace{0.167em} \psi = 0$ on $D$ is analysed, where $v$ is a smooth real-valued potential of conductivity type defined on a bounded planar domain $D$. The main feature of this estimate is that it shows that the smoother a potential is, the more stable its reconstruction is. Furthermore, the stability is proven to depend exponentially on the smoothness, in a sense to be made precise. The same techniques yield a similar estimate for the Calderón problem for electrical impedance tomography.

This paper analyzes the continuum model/complete electrode model in the electricalimpedance tomography inverse problem of determining the conductivity parameter fromboundary measurements. The continuity and differentiability of the forward operator withrespect to the conductivity parameter inLp-norms are proved. These analytical resultsare applied to several popular regularization formulations, which incorporate apriori information of smoothness/sparsity on the inhomogeneity through Tikhonovregularization, for both linearized and nonlinear models. Some important properties,e.g., existence, stability, consistency andconvergence rates, are established. This provides some theoretical justifications of theirpractical usage.

We consider the problem of electrical impedance tomography where conductivity distribution in a domain is to be reconstructed from boundary measurements of voltage and currents. It is well-known that this problem is highly illposed. In this work, we propose the use of the Mumford–Shah functional, developed for segmentation and denoising of images, as a regularization. After establishing existence properties of the resulting variational problem, we proceed by demonstrating the approach in several numerical examples. Our results indicate that this is an effective approach for overcoming the illposedness. Moreover, it has the capability of enhancing the reconstruction while at the same time segmenting the conductivity image.