Comparison of statistical inversion with iteratively regularized Gauss Newton method for image reconstruction in electrical impedance tomography

DOI10.1016/j.amc.2019.03.063zbMath1428.78036OpenAlexW2944413607WikidataQ127901724 ScholiaQ127901724MaRDI QIDQ2279381

Thilo Strauss, Taufiquar Khan, Shyla Kupis, Sanwar Ahmad

Publication date: 12 December 2019

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2019.03.063

zbMATH Keywords

Metropolis-Hastings algorithmelectrical impedance tomographyBayesian inversionstatistical inversionMarkov chain Monte-Carlo method

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Technical applications of optics and electromagnetic theory (78A55) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21) Basic methods for problems in optics and electromagnetic theory (78M99)

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Cites Work

• Unnamed Item
• Statistical inversion in electrical impedance tomography using mixed total variation and non-convex \(\ell_{p}\) regularization prior
• Gabor analysis of the continuum model for impedance tomography
• 1D inverse problem in diffusion based optical tomography using iteratively regularized Gauss--Newton algorithm
• A reconstruction algorithm for electrical impedance tomography based on sparsity regularization
• MCMC-Based Image Reconstruction with Uncertainty Quantification
• Posterior covariance related optimal current patterns in electrical impedance tomography
• Newton regularizations for impedance tomography: a numerical study
• Existence and Uniqueness for Electrode Models for Electric Current Computed Tomography
• Numerical Optimization
• Electrical Impedance Tomography
• Recent progress in electrical impedance tomography
• Statistical inversion and Monte Carlo sampling methods in electrical impedance tomography
• Adaptive Markov Chain Monte Carlo through Regeneration
• A note on convergence of solutions of total variation regularized linear inverse problems
• Can one use total variation prior for edge-preserving Bayesian inversion?
• ON APPLICATION OF GENERALIZED DISCREPANCY PRINCIPLE TO ITERATIVE METHODS FOR NONLINEAR ILL-POSED PROBLEMS
• Electrical impedance tomography
• An analysis of electrical impedance tomography with applications to Tikhonov regularization
• Sparsity regularization for parameter identification problems
• Fast Markov chain Monte Carlo sampling for sparse Bayesian inference in high-dimensional inverse problems using L1-type priors
• Convergence and application of a modified iteratively regularized Gauss–Newton algorithm
• An adaptive Metropolis algorithm

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