Uniqueness and convergence of conductivity image reconstruction in magnetic resonance electrical impedance tomography
From MaRDI portal
Publication:4460656
DOI10.1088/0266-5611/19/5/312zbMath1054.35134OpenAlexW2157877884MaRDI QIDQ4460656
Jin-Keun Seo, Oh In Kwon, Eung Je Woo, Yong-Jung Kim
Publication date: 18 May 2004
Published in: Inverse Problems (Search for Journal in Brave)
Full work available at URL: https://semanticscholar.org/paper/8a5372f641f83ac093070e3705fb3bd77868af3d
PDEs in connection with optics and electromagnetic theory (35Q60) Inverse problems for PDEs (35R30) Laplace operator, Helmholtz equation (reduced wave equation), Poisson equation (35J05)
Related Items
A fully non-linear optimization approach to acousto-electric tomography ⋮ Well-posedness of the conductivity reconstruction from an interior current density in terms of Schauder theory ⋮ Mathematical framework for current density imaging due to discharge of electro-muscular disruption devices ⋮ Convergence Analysis of the Harmonic \(\boldsymbol{B_{{z}}}\) Algorithm with Single Injection Current in MREIT ⋮ Existence and uniqueness in anisotropic conductivity reconstruction with Faraday's law ⋮ A uniqueness result and image reconstruction of the orthotropic conductivity in magnetic resonance electrical impedance tomography ⋮ Electrical networks with prescribed current and applications to random walks on graphs ⋮ Mathematical framework for \(B_{z}\)-based MREIT model in electrical impedance imaging ⋮ Expansion Methods ⋮ Orthotropic conductivity reconstruction with virtual-resistive network and Faraday's law ⋮ Numerical conductivity reconstruction from partial interior current density information in three dimensions ⋮ Sparse reconstruction of log-conductivity in current density impedance tomography ⋮ Mathematical models and reconstruction methods in magneto-acoustic imaging ⋮ Towards monitoring critical microscopic parameters for electropermeabilization ⋮ Conductivity imaging with interior potential measurements ⋮ Resistivity Tensor Imaging via Network Discretization of Faraday's Law
