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We consider the linearized electrical impedance tomography problem in two dimensions on the unit disk. By a linearization around constant coefficients and using a trigonometric basis, we calculate the linearized Dirichlet-to-Neumann…

Numerical Analysis · Mathematics 2017-06-08 Stefan Kindermann

This short note modifies a reconstruction method by the author (Comm. PDE, 45(9):1118-1133, 2020), for reconstructing piecewise constant conductivities in the Calder\'on problem (electrical impedance tomography). In the former paper, a…

Analysis of PDEs · Mathematics 2025-12-08 Henrik Garde

Working within the class of piecewise constant conductivities, the inverse problem of electrical impedance tomography can be recast as a shape optimization problem where the discontinuity interface is the unknown. Using Gr\"oger's…

Optimization and Control · Mathematics 2022-01-28 Yuri Flores Albuquerque , Antoine Laurain , Kevin Sturm

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

This short note considerably simplifies a reconstruction method by the author (Comm. PDE, 45(9):1118--1133, 2020), for reconstructing piecewise constant layered conductivities (PCLC) from partial boundary measurements in electrical…

Analysis of PDEs · Mathematics 2022-08-24 Henrik Garde

We consider the problem of reconstructing of the boundary of an unknown inclusion together with its conductivity from the localized Dirichlet-to-Neumann map. We give an exact reconstruction procedure and apply the method to an inverse…

Analysis of PDEs · Mathematics 2018-03-09 Masaru Ikehata

This paper concerns a fast, one-step iterative technique of imaging extended perfectly conducting cracks with Dirichlet boundary condition. In order to reconstruct the shape of cracks from scattered field data measured at the boundary, we…

Mathematical Physics · Physics 2017-04-13 Won-Kwang Park

This paper introduces a new approach for solving electrical impedance tomography (EIT) problems using deep neural networks. The mathematical problem of EIT is to invert the electrical conductivity from the Dirichlet-to-Neumann (DtN) map.…

Computational Physics · Physics 2020-01-29 Yuwei Fan , Lexing Ying

We study the numerical reconstruction problem in acousto-electric tomography of recovering the conductivity distribution in a bounded domain from interior power density data. We propose a numerical method for recovering discontinuous…

Optimization and Control · Mathematics 2019-02-20 Bolaji James Adesokan , Bjørn Jensen , Bangti Jin , Kim Knudsen

In Electrical Impedance Tomography (EIT), the internal conductivity of a body is recovered via current and voltage measurements taken at its surface. The reconstruction task is a highly ill-posed nonlinear inverse problem, which is very…

Numerical Analysis · Mathematics 2018-03-28 Sarah Hamilton , Andreas Hauptmann , Samuli Siltanen

In this paper, we investigate a non-iterative imaging algorithm based on the topological derivative in order to retrieve the shape of penetrable electromagnetic inclusions when their dielectric permittivity and/or magnetic permeability…

Mathematical Physics · Physics 2013-05-14 Won-Kwang Park

A novel computational, non-iterative and noise-robust reconstruction method is introduced for the planar anisotropic inverse conductivity problem. The method is based on bypassing the unstable step of the reconstruction of the values of the…

Analysis of PDEs · Mathematics 2015-06-25 Sarah Jane Hamilton , Matti Lassas , Samuli Siltanen

Electron tomography is becoming an increasingly important tool in materials science for studying the three-dimensional morphologies and chemical compositions of nanostructures. The image quality obtained by many current algorithms is…

We are aiming to identify the thin insulating inhomogeneities and small conductive inhomogeneities inside an electrically conducting medium by using multi-frequency electrical impedance tomography (mfEIT). The thin insulating…

Analysis of PDEs · Mathematics 2016-08-24 Habib Ammari , Jin Keun Seo , Tingting Zhang

This paper investigates the shape reconstructions of sub-wavelength objects from near-field measurements in transverse electromagnetic scattering. This geometric inverse problem is notoriously ill-posed and challenging. We develop a novel…

Mathematical Physics · Physics 2023-05-03 M. H. Ding , H. Y. Liu , G. H. Zheng

In this study, we investigate the inverse source problem arising in bioluminescence tomography, the objective of which is to reconstruct both the support and the intensity of an internal light source from boundary measurements governed by…

Numerical Analysis · Mathematics 2025-11-25 Qianqian Wu , Rongfang Gong , Wei Gong , Ziyi Zhang , Shengfeng Zhu

Electrical impedance tomography (EIT) is an imaging modality in which the conductivity distribution inside a target is reconstructed based on voltage measurements from the surface of the target. Reconstructing the conductivity distribution…

Mathematical Physics · Physics 2012-07-05 Antti Lipponen , Aku Seppänen , Jari Kaipio

We provide a mathematical analysis and a numerical framework for magnetoacoustic tomography with magnetic induction. The imaging problem is to reconstruct the conductivity distribution of biological tissue from measurements of the Lorentz…

Analysis of PDEs · Mathematics 2015-08-05 Habib Ammari , Simon Boulier , Pierre Millien

In this paper we develop theoretical analysis and numerical reconstruction techniques for the solution of an inverse boundary value problem dealing with the nonlinear, time-dependent monodomain equation, which models the evolution of the…

Analysis of PDEs · Mathematics 2017-01-27 Elena Beretta , Cecilia Cavaterra , Maria Cristina Cerutti , Andrea Manzoni , Luca Ratti

Optimization in engineering requires appropriate models. In this article, a regression method for enhancing the predictive power of a model by exploiting expert knowledge in the form of shape constraints, or more specifically, monotonicity…