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The aim of hybrid inverse problems such as Acousto-Electric Tomography or Current Density Imaging is the reconstruction of the electrical conductivity in a domain that can only be accessed from its exterior. In the inversion procedure, the…

泛函分析 · 数学 2023-10-12 Mikko Salo , Hjørdis Schlüter

This paper considers the reconstruction problem in Acousto-Electrical Tomography, i.e., the problem of estimating a spatially varying conductivity in a bounded domain from measurements of the internal power densities resulting from…

数值分析 · 数学 2020-01-13 Simon Hubmer , Kim Knudsen , Changyou Li , Ekaterina Sherina

In Acousto-Electric tomography, the objective is to extract information about the interior electrical conductivity in a physical body from knowledge of the interior power density data generated from prescribed boundary conditions for the…

偏微分方程分析 · 数学 2022-07-26 Bjørn Jensen , Kim Knudsen , Hjørdis Schlüter

This paper considers the non-linear inverse problem of reconstructing an electric conductivity distribution from the interior power density in a bounded domain. Applications include the novel tomographic method known as acousto-electric…

最优化与控制 · 数学 2018-08-29 B. J. Adesokan , Kim Knudsen , Venkateswaran P. Krishnan , Souvik Roy

In acousto-electric tomography the goal is to reconstruct the electric conductivity in a domain from electrostatic boundary measurements of corresponding currents and voltages, while the domain is penetrated by a time-dependent acoustic…

医学物理 · 物理学 2024-02-01 Bjørn Jensen , Adrian Kirkeby , Kim Knudsen

Hybrid inverse problems are based on the interplay of two types of waves, in order to allow for imaging with both high resolution and high contrast. The inversion procedure often consists of two steps: first, internal measurements involving…

偏微分方程分析 · 数学 2022-10-14 Giovanni S. Alberti

We propose and test stable algorithms for the reconstruction of the internal conductivity of a biological object using acousto-electric measurements. Namely, the conventional impedance tomography scheme is supplemented by scanning the…

偏微分方程分析 · 数学 2015-05-20 Peter Kuchment , Leonid Kunyansky

Acousto-electric tomography (AET) is a hybrid imaging modality that combines electrical impedance tomography with focused ultrasound perturbations to obtain interior power density measurements, which provide additional information that can…

偏微分方程分析 · 数学 2026-03-31 Hjørdis Schlüter , Babak Maboudi Afkham

The inverse problem in Acousto-Electric tomography concerns the reconstruction of the electric conductivity in a domain from knowledge of the power density function in the interior of the body. This interior power density results from…

数值分析 · 数学 2020-01-09 Changyou Li , Mirza Karamehmedovic , Ekaterina Sherina , Kim Knudsen

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…

最优化与控制 · 数学 2019-02-20 Bolaji James Adesokan , Bjørn Jensen , Bangti Jin , Kim Knudsen

This paper focuses on the acousto-electromagnetic tomography, a recently introduced hybrid imaging technique. In a previous work, the reconstruction of the electric permittivity of the medium from internal data was achieved under the Born…

偏微分方程分析 · 数学 2019-04-04 Giovanni S. Alberti , Habib Ammari , Kaixi Ruan

This letter announces and summarizes results obtained in arXiv:1111.5051 and considers several natural extensions. The aforementioned paper proposes a procedure to reconstruct coefficients in a second-order, scalar, elliptic equation from…

偏微分方程分析 · 数学 2012-03-07 Guillaume Bal , Gunther Uhlmann

In Electrical Impedance Tomography (EIT) one wants to image the conductivity distribution of a body from current and voltage measurements carried out on its boundary. In this paper we consider the underlying mathematical model, the inverse…

数值分析 · 数学 2017-04-10 Andreas Hauptmann , Matteo Santacesaria , Samuli Siltanen

We consider the imaging of anisotropic conductivity tensors $\gamma=(\gamma_{ij})_{1\leq i,j\leq 2}$ from knowledge of several internal current densities $\mathcal{J}=\gamma\nabla u$ where $u$ satisfies a second order elliptic equation…

偏微分方程分析 · 数学 2014-03-21 Guillaume Bal , Chenxi Guo , François Monard

Electrical impedance tomography aims at reconstructing the conductivity inside a physical body from boundary measurements of current and voltage at a finite number of contact electrodes. In many practical applications, the shape of the…

数值分析 · 数学 2017-03-08 Nuutti Hyvönen , Helle Majander , Stratos Staboulis

In this paper, we consider an inverse conductivity problem on a bounded domain $\Omega\subset\mathbb{R}^n$, $n\geq2$, also known as Electrical Impedance Tomography (EIT), for the case where unknown impenetrable obstacles are embedded into…

偏微分方程分析 · 数学 2021-04-29 Jiaqing Yang

Consider an inverse problem of the simultaneous recovery of boundary impedance and internal conductivity in the electrical impedance tomography (EIT) model using local internal measurement data, which is governed by a boundary value problem…

偏微分方程分析 · 数学 2025-09-22 Jinchao Pan , Jijun Liu

Multi-wave inverse problems are indirect imaging methods using the interaction of two different imaging modalities. One brings spatial accuracy, and the other contrast sensitivity. The inversion method typically involve two steps. The first…

偏微分方程分析 · 数学 2023-01-05 Yves Capdeboscq , Tianrui Dai

In this paper we the formulation of inverse problems as constrained minimization problems and their iterative solution by gradient or Newton type. We carry out a convergence analysis in the sense of regularization methods and discuss…

数值分析 · 数学 2021-01-15 Barbara Kaltenbacher , Kha Van Huynh

The aim of electrical impedance tomography is to reconstruct the admittivity distribution inside a physical body from boundary measurements of current and voltage. Due to the severe ill-posedness of the underlying inverse problem, the…

偏微分方程分析 · 数学 2022-07-19 Jérémi Dardé , Nuutti Hyvönen , Aku Seppänen , Stratos Staboulis
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