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Electrical impedance tomography (EIT) is a non-invasive imaging method with diverse applications, including medical imaging and non-destructive testing. The inverse problem of reconstructing internal electrical conductivity from boundary…

Image and Video Processing · Electrical Eng. & Systems 2025-07-08 Sara Sippola , Siiri Rautio , Andreas Hauptmann , Takanori Ide , Samuli Siltanen

The aim of Electrical Impedance Tomography (EIT) is to determine the electrical conductivity distribution inside a domain by applying currents and measuring voltages on its boundary. Mathematically, the EIT reconstruction task can be…

Numerical Analysis · Mathematics 2024-05-07 Monica Pragliola , Daniela Calvetti , Erkki Somersalo

In a previous paper (J. Comp. Phys. 230 (2011), 3668--3694), the authors proposed a new practical method for computing expected values of functionals of solutions for certain classes of elliptic partial differential equations with random…

Numerical Analysis · Mathematics 2018-04-03 Ivan G. Graham , Frances Y. Kuo , Dirk Nuyens , Rob Scheichl , Ian H. Sloan

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

Electrical impedance tomography (EIT) is a non-invasive imaging technique, capable of reconstructing images of the electrical conductivity of tissues and materials. It is popular in diverse application areas, from medical imaging to…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Shuaikai Shi , Ruiyuan Kang , Panos Liatsis

Two reconstruction methods of Electrical Impedance Tomography (EIT) are numerically compared for nonsmooth conductivities in the plane based on the use of complex geometrical optics (CGO) solutions to D-bar equations involving the global…

Analysis of PDEs · Mathematics 2015-06-17 Kari Astala , Lassi Päivärinta , Juan Manuel Reyes , Samuli Siltanen

Electrical Impedance Tomography (EIT) is a non-invasive, low-cost bedside imaging modality with high temporal resolution, making it suitable for bedside monitoring. However, its inherently ill-posed inverse problem poses significant…

Computer Vision and Pattern Recognition · Computer Science 2025-07-21 Hao Fang , Sihao Teng , Hao Yu , Siyi Yuan , Huaiwu He , Zhe Liu , Yunjie Yang

Quasi-Monte Carlo (QMC) methods are applied to multi-level Finite Element (FE) discretizations of elliptic partial differential equations (PDEs) with a random coefficient, to estimate expected values of linear functionals of the solution.…

Numerical Analysis · Mathematics 2014-05-16 Frances Y. Kuo , Christoph Schwab , Ian H. Sloan

Unknown electric conductivities of human tissues is a common issue in medical engineering. Electrical impedance tomography (EIT) is an imaging modality that can be used to determine these conductivities in vivo from boundary measurements.…

Medical Physics · Physics 2020-02-03 Ville Rimpilainen , Theodoros Samaras , Alexandra Koulouri

We propose a new numerical method to reconstruct the isotropic electrical conductivity from measured restricted Dirichlet-to-Neumann map data in electrical impedance tomography (EIT) model. "Restricted Dirichlet-to-Neumann (DtN) map data"…

Numerical Analysis · Mathematics 2019-02-20 Michael V. Klibanov , Jingzhi Li , Wenlong Zhang

In this paper, we consider the numerical solution of a nonlinear Schrodinger equation with spatial random potential. The randomly shifted quasi-Monte Carlo (QMC) lattice rule combined with the time-splitting pseudospectral discretization is…

Numerical Analysis · Mathematics 2023-11-21 Zhizhang Wu , Zhiwen Zhang , Xiaofei Zhao

Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the boundary of a conductive medium (the data) are taken according to a prescribed protocol set and inverted to map the internal…

In this study, we consider the development of tailored quasi-Monte Carlo (QMC) cubatures for non-conforming discontinuous Galerkin (DG) approximations of elliptic partial differential equations (PDEs) with random coefficients. We consider…

Numerical Analysis · Mathematics 2024-12-12 Vesa Kaarnioja , Andreas Rupp

We study the application of a tailored quasi-Monte Carlo (QMC) method to a class of optimal control problems subject to parabolic partial differential equation (PDE) constraints under uncertainty: the state in our setting is the solution of…

Numerical Analysis · Mathematics 2024-03-28 Philipp A. Guth , Vesa Kaarnioja , Frances Y. Kuo , Claudia Schillings , Ian H. Sloan

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…

Analysis of PDEs · Mathematics 2020-08-18 Henrik Garde

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

Quasi-Monte Carlo (QMC) integration of output functionals of solutions of the diffusion problem with a log-normal random coefficient is considered. The random coefficient is assumed to be given by an exponential of a Gaussian random field…

Numerical Analysis · Mathematics 2017-01-24 Yoshihito Kazashi

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

Conservation laws in the form of elliptic and parabolic partial differential equations (PDEs) are fundamental to the modeling of many problems such as heat transfer and flow in porous media. Many of such PDEs are stochastic due to the…

Computational Physics · Physics 2018-11-19 Amir H. Delgoshaie , Peter W. Glynn , Patrick Jenny , Hamdi A. Tchelepi

We analyse and implement a quasi-Monte Carlo (QMC) finite element method (FEM) for the forward problem of uncertainty quantification (UQ) for the Helmholtz equation with random coefficients, both in the second-order and zero-order terms of…

Numerical Analysis · Mathematics 2025-11-04 Ivan G. Graham , Frances Y. Kuo , Dirk Nuyens , Ian H. Sloan , Euan A. Spence