# Generalized linearization techniques in electrical impedance tomography

## TL;DR

This paper compares various linearization methods in electrical impedance tomography, introduces a new technique based on the logarithm of the Neumann-to-Dirichlet operator, and demonstrates its improved accuracy through numerical examples.

## Contribution

It proposes a novel linearization approach using the logarithm of the Neumann-to-Dirichlet operator, enhancing accuracy in electrical impedance tomography reconstructions.

## Key findings

- Conductivity linearization often reduces accuracy.
- Logarithmic linearization improves forward and inverse problem solutions.
- Numerical results confirm the effectiveness of the new method.

## Abstract

Electrical impedance tomography aims at reconstructing the interior electrical conductivity from surface measurements of currents and voltages. As the current-voltage pairs depend nonlinearly on the conductivity, impedance tomography leads to a nonlinear inverse problem. Often, the forward problem is linearized with respect to the conductivity and the resulting linear inverse problem is regarded as a subproblem in an iterative algorithm or as a simple reconstruction method as such. In this paper, we compare this basic linearization approach to linearizations with respect to the resistivity or the logarithm of the conductivity. It is numerically demonstrated that the conductivity linearization often results in compromised accuracy in both forward and inverse computations. Inspired by these observations, we present and analyze a new linearization technique which is based on the logarithm of the Neumann-to-Dirichlet operator. The method is directly applicable to discrete settings, including the complete electrode model. We also consider Fr\'echet derivatives of the logarithmic operators. Numerical examples indicate that the proposed method is an accurate way of linearizing the problem of electrical impedance tomography.