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相关论文: Adaptive Reconstruction for Electrical Impedance T…

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In this work we develop and analyze an adaptive finite element method for efficiently solving electrical impedance tomography -- a severely ill-posed nonlinear inverse problem for recovering the conductivity from boundary voltage…

数值分析 · 数学 2019-05-16 Bangti Jin , Yifeng Xu , Jun Zou

We present a finite element analysis of electrical impedance tomography for reconstructing the conductivity distribution from electrode voltage measurements by means of Tikhonov regularization. Two popular choices of the penalty term, i.e.,…

数值分析 · 数学 2015-06-18 Matthias Gehre , Bangti Jin , Xiliang Lu

Electrical impedance tomography is an imaging modality for extracting information on the conductivity distribution inside a physical body from boundary measurements of current and voltage. In many practical applications, it is a priori…

数值分析 · 数学 2014-06-06 Lauri Harhanen , Nuutti Hyvönen , Helle Majander , Stratos Staboulis

In this paper we investigate the problem of identifying conductivity in electrical impedance tomography from one boundary measurement. A variational method with total variation regularization is here proposed to tackle this problem. We…

偏微分方程分析 · 数学 2017-09-26 Michael Hinze , Barbara Kaltenbacher , Tran Nhan Tam Quyen

The aim of electrical impedance tomography is to form an image of the conductivity distribution inside an unknown body using electric boundary measurements. The computation of the image from measurement data is a non-linear ill-posed…

数值分析 · 数学 2011-09-28 Samuli Siltanen , Janne P. Tamminen

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

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

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…

偏微分方程分析 · 数学 2018-09-20 Henrik Garde , Stratos Staboulis

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

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

We propose an adaptive finite element method for the solution of a coefficient inverse problem of simultaneous reconstruction of the dielectric permittivity and magnetic permeability functions in the Maxwell's system using limited boundary…

数值分析 · 数学 2016-01-26 Larisa Beilina , Samar Hosseinzadegan

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…

数值分析 · 数学 2016-01-20 Henrik Garde , Kim Knudsen

This work presents a new constructive uniqueness proof for Calder\'on's inverse problem of electrical impedance tomography, subject to local Cauchy data, for a large class of piecewise constant conductivities that we call "piecewise…

偏微分方程分析 · 数学 2020-08-18 Henrik Garde

In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal partition from boundary measurements. The key tool is to…

偏微分方程分析 · 数学 2018-03-20 Elena Beretta , Stefano Micheletti , Simona Perotto , Matteo Santacesaria

We consider a coefficient inverse problem for the dielectric permittivity in Maxwell's equations, with data consisting of boundary measurements of one or two backscattered or transmitted waves. The problem is treated using a Lagrangian…

数值分析 · 数学 2016-03-18 John Bondestam Malmberg , Larisa Beilina

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…

偏微分方程分析 · 数学 2025-12-08 Henrik Garde

The monotonicity-based approach has become one of the fundamental methods for reconstructing inclusions in the inverse problem of electrical impedance tomography. Thus far the method has not been proven to be able to handle extreme…

偏微分方程分析 · 数学 2021-02-05 Valentina Candiani , Jérémi Dardé , Henrik Garde , Nuutti Hyvönen

We study the Electrical Impedance Tomography Bayesian inverse problem for recovering the conductivity given noisy measurements of the voltage on some boundary surface electrodes. The uncertain conductivity depends linearly on a countable…

数值分析 · 数学 2023-06-16 Quang Huy Pham , Viet Ha Hoang

Physics has played a fundamental role in medicine sciences, specially in imaging diagnostic. Currently, image reconstruction techniques are already taught in Physics courses and there is a growing interest in new potential applications. The…

物理教育 · 物理学 2013-02-22 Olavo Henrique Menin , Vanessa Rolnik , Alexandre Souto Martinez

Conductivity reconstruction in an inverse eddy current problem is considered in the present paper. With the electric field measurement on part of domain boundary, we formulate the reconstruction problem to a constrained optimization problem…

数值分析 · 数学 2023-07-04 Junqing Chen , Zehao Long
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