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By introducing a shape manifold as a solution set to solve inverse obstacle scattering problems we allow the reconstruction of general, not necessarily star-shaped curves. The bending energy is used as a stabilizing term in Tikhonov…

Numerical Analysis · Mathematics 2020-01-08 Julian Eckhardt , Ralf Hiptmair , Thorsten Hohage , Henrik Schumacher , Max Wardetzky

This paper introduces a method for approximately eliminating the effect that conductivity changes outside the region of interest have in electrical impedance tomography, allowing to form a local reconstruction in the region of interest…

Numerical Analysis · Mathematics 2026-01-21 A. Jääskeläinen , A. Vavilov , J. Toivanen , A. Hänninen , V. Kolehmainen , N. Hyvönen

A new non-linear optimization approach is proposed for the sparse reconstruction of log-conductivities in current density impedance imaging. This framework comprises of minimizing an objective functional involving a least squares fit of the…

Optimization and Control · Mathematics 2020-06-30 Madhu Gupta , Rohit Kumar Mishra , Souvik Roy

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 paper presents a regularization technique for the high order efficient numerical evaluation of nearly singular, principal-value, and finite-part Cauchy-type integral operators. By relying on the Cauchy formula, the Cauchy-Goursat…

Numerical Analysis · Mathematics 2021-03-02 Vicente Gómez , Carlos Pérez-Arancibia

The use of ray projections to reconstruct images is a common technique in medical imaging. Dealing with incomplete data is particularly important when a patient is vulnerable to potentially damaging radiation or is unable to cope with the…

Neural and Evolutionary Computing · Computer Science 2024-06-04 Mohammad Majid al-Rifaie , Tim Blackwell

Let X be a compact complex manifold equipped with a smooth (but not necessarily positive) closed form theta of one-one type. By a well-known envelope construction this data determines a canonical theta-psh function u which is not two times…

Complex Variables · Mathematics 2017-02-23 Robert J. Berman

Many applications in vision require estimation of thin structures such as boundary edges, surfaces, roads, blood vessels, neurons, etc. Unlike most previous approaches, we simultaneously detect and delineate thin structures with sub-pixel…

Computer Vision and Pattern Recognition · Computer Science 2017-05-23 Dmitrii Marin , Yuri Boykov , Yuchen Zhong

Linear inverse problems are ubiquitous. Often the measurements do not follow a Gaussian distribution. Additionally, a model matrix with a large condition number can complicate the problem further by making it ill-posed. In this case, the…

In this article, we consider the problem of finding the support of an inhomogenous possibly anisotropic inclusion in a background of constant electric conductivity from the electrical impedance tomography data at the boundary of a bounded…

Functional Analysis · Mathematics 2007-05-23 Erkki J. Somersalo

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

The ill-posedness of Calder\'on's inverse conductivity problem, responsible for the poor spatial resolution of Electrical Impedance Tomography (EIT), has been an impetus for the development of hybrid imaging techniques, which compensate for…

Analysis of PDEs · Mathematics 2021-04-28 Allan Greenleaf , Matti Lassas , Matteo Santacesaria , Samuli Siltanen , Gunther Uhlmann

In this paper, we consider the efficient numerical minimization of Tikhonov functionals resulting from total-variation (TV) regularization of linear inverse problems. Since the TV penalty is non-smooth, this is typically done either via…

Numerical Analysis · Mathematics 2026-05-13 Helmut Gfrerer , Simon Hubmer , Stefan Kindermann , Jaakko Kultima , Ronny Ramlau , Tanja Tarvainen

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…

Numerical Analysis · Mathematics 2023-07-04 Junqing Chen , Zehao Long

We generalise the $\eta$ regularisation scheme in order to develop a framework for systematically studying regularisation of loops in quantum field theory. This allows us to "solve" a set of gauge consistency conditions for families of…

High Energy Physics - Theory · Physics 2024-12-18 Antonio Padilla , Robert G. C. Smith

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

Optimization and Control · Mathematics 2018-09-18 Ugur G. Abdulla , Vladislav Bukshtynov , Saleheh Seif

This paper focuses on the time-harmonic electromagnetic (EM) scattering problem in a general medium which may possess a nontrivial topological structure. We model this by an inhomogeneous and possibly anisotropic medium with embedded…

Analysis of PDEs · Mathematics 2024-08-14 Huaian Diao , Hongyu Liu , Qingle Meng , Li Wang

We consider the electrostatic inverse boundary value problem also known as electrical impedance tomography (EIT) for the case where the conductivity is a piecewise linear function on a domain $\Omega\subset\mathbb{R}^n$ and we show that a…

Analysis of PDEs · Mathematics 2016-11-03 Giovanni Alessandrini , Maarten V. de Hoop , Romina Gaburro , Eva Sincich

We develop a method for optimization in shape spaces, i.e., sets of surfaces modulo re-parametrization. Unlike previously proposed gradient flows, we achieve superlinear convergence rates through a subtle approximation of the shape Hessian,…

Computer Vision and Pattern Recognition · Computer Science 2014-04-15 J. Balzer , S. Soatto

The common graph Laplacian regularizer is well-established in semi-supervised learning and spectral dimensionality reduction. However, as a first-order regularizer, it can lead to degenerate functions in high-dimensional manifolds. The…

Computer Vision and Pattern Recognition · Computer Science 2016-02-12 Kwang In Kim , James Tompkin , Hanspeter Pfister , Christian Theobalt