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The inverse problem of electrical impedance tomography is severely ill-posed, meaning that, only limited information about the conductivity can in practice be recovered from boundary measurements of electric current and voltage. Recently it…

Analysis of PDEs · Mathematics 2018-09-20 Henrik Garde , Stratos Staboulis

Based upon elements of the modern Pseudoanalytic Function Theory, we analyse a new method for numerically approaching the solution of the Dirichlet boundary value problem, corresponding to the two-dimensional Electrical Impedance Equation.…

Mathematical Physics · Physics 2012-02-23 M. P. Ramirez T. , C. M. A. Robles G. , R. A. Hernandez-Becerril

In this paper, we will discuss the use of a Sampling Method to reconstruct impenetrable inclusions from Electrostatic Cauchy data. We consider the case of a perfectly conducting and impedance inclusion. In either case, we show that the…

Analysis of PDEs · Mathematics 2021-02-10 Isaac Harris

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…

Numerical Analysis · Mathematics 2017-05-31 Nuutti Hyvönen , Lauri Mustonen

Inverse problems for Partial Differential Equations (PDEs) are crucial in numerous applications such as geophysics, biomedical imaging, and material science, where unknown physical properties must be inferred from indirect measurements. In…

Numerical Analysis · Mathematics 2025-11-12 Dabin Park , Sanghyun Lee , Sunghwan Moon

In this paper, we derive a Sampling Method to solve the inverse shape problem of recovering an inclusion with a generalized impedance condition from electrostatic Cauchy data. The generalized impedance condition is a second-order…

Analysis of PDEs · Mathematics 2019-05-30 Isaac Harris

This paper considers the problem of noise-robust neural operator approximation for the solution map of Calder\'on's inverse conductivity problem. In this continuum model of electrical impedance tomography (EIT), the boundary measurements…

Numerical Analysis · Mathematics 2025-11-26 Maarten V. de Hoop , Nikola B. Kovachki , Matti Lassas , Nicholas H. Nelsen

We show how to eliminate the error caused by an incorrectly modeled boundary in electrical impedance tomography (EIT). In practical measurements, one usually lacks the exact knowledge of the boundary. Because of this the numerical…

Analysis of PDEs · Mathematics 2007-05-23 Ville Kolehmainen , Matti Lassas , Petri Ola

The problem of characterizing sequences of real numbers that arise as spectra of Dirichlet-to-Neumann (DtN) maps for elliptic operators has attracted considerable attention over the past fifty years. In this article, we address this…

Analysis of PDEs · Mathematics 2026-02-02 Thierry Daudé , Fabricio Macià , Cristóbal Meroño , François Nicoleau

A positive function (conductivity) on the edges of a graph induces the Dirichlet-to- Neumann map between boundary values of harmonic functions. The inverse conductivity problem is to find the conductivity from the Dirichlet-to-Neumann map.…

General Mathematics · Mathematics 2010-03-05 David V. Ingerman

We consider Inverse Electrical Impedance Tomography (EIT) problem on recovering electrical conductivity and potential in the body based on the measurement of the boundary voltages on the $m$ electrodes for a given electrode current. The…

Optimization and Control · Mathematics 2024-12-17 Ugur G. Abdulla , Saleheh Seif

The unique determination of electrical conductivity is extensively studied for isotropic conductivity ever since Calderon's suggestion of the EIT (Electrical Impedance Tomography) problem. However, it is known that there are many…

Analysis of PDEs · Mathematics 2013-04-25 Kiwoon Kwon

The paper concerns the isotropic interior transmission eigenvalue (ITE) problem. This problem is not elliptic, but we show that, using the Dirichlet-to-Neumann map, it can be reduced to an elliptic one. This leads to the discreteness of the…

Mathematical Physics · Physics 2015-06-12 Evgeny Lakshtanov , Boris Vainberg

We show that measurements of the Neumann-to-Dirichlet map, roughly speaking, on a certain part of the boundary of a smooth domain in dimension 3 or higher, for inputs with support restricted to the other part, determine an electric…

Analysis of PDEs · Mathematics 2013-10-22 Francis J. Chung

The objective of electrical impedance tomography (EIT) is to reconstruct the internal conductivity of a physical body based on current and voltage measurements at the boundary of the body. In many medical applications the exact shape of the…

Optimization and Control · Mathematics 2021-10-25 J. P. Agnelli , V. Kolehmainen , M. Lassas , P. Ola , S. Siltanen

Some linear integro-differential operators have old and classical representations as the Dirichlet-to-Neumann operators for linear elliptic equations, such as the 1/2-Laplacian or the generator of the boundary process of a reflected…

Analysis of PDEs · Mathematics 2017-10-10 Nestor Guillen , Jun Kitagawa , Russell W. Schwab

We treat an inverse electrical conductivity problem which deals with the reconstruction of nonlinear electrical conductivity starting from boundary measurements in steady currents operations. In this framework, a key role is played by the…

In electrical impedance tomography the electrical conductivity inside a physical body is computed from electro-static boundary measurements. The focus of this paper is to extend recent result for the 2D problem to 3D. Prior information…

Numerical Analysis · Mathematics 2016-01-20 Henrik Garde , Kim Knudsen

We review a resistor network approach to the numerical solution of the inverse problem of electrical impedance tomography (EIT). The networks arise in the context of finite volume discretizations of the elliptic equation for the electric…

Mathematical Physics · Physics 2015-06-03 Liliana Borcea , Vladimir Druskin , Fernando Guevara Vasquez , Alexander V. Mamonov

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning…

Machine Learning · Computer Science 2026-01-27 Adrienne M. Propp , Jonas A. Actor , Elise Walker , Houman Owhadi , Nathaniel Trask , Daniel M. Tartakovsky