Adaptive reconstruction for electrical impedance tomography with a piecewise constant conductivity

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Abstract

In this work we propose and analyze a numerical method for electrical impedance tomography to recover a piecewise constant conductivity from boundary voltage measurements. It is based on standard Tikhonov regularization with a Modica-Mortola penalty functional and adaptive mesh refinement using suitable a posteriori error estimators of residual type that involve the state, adjoint and variational inequality in the necessary optimality condition and a separate marking strategy. We prove the convergence of the adaptive algorithm in the following sense: the sequence of discrete solutions contains a subsequence convergent to a solution of the continuous necessary optimality system. Several numerical examples are presented to illustrate the convergence behavior of the algorithm.

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APA

Jin, B., & Xu, Y. (2020). Adaptive reconstruction for electrical impedance tomography with a piecewise constant conductivity. Inverse Problems, 36(1). https://doi.org/10.1088/1361-6420/ab261e

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