Journal Article


Sparse 3D reconstructions in electrical Impedance Tomography using real data

Abstract

We present a 3D reconstruction algorithm with sparsity constraints for Electrical Impedance Tomography (EIT). EIT is the inverse problem of determining the distribution of conductivity in the interior of an object from simultaneous measurements of currents and voltages on its boundary. The feasibility of the sparsity reconstruction approach is tested with real data obtained from a new planar EIT device developed at the Institut für Physik, Johannes Gutenberg Universität, Mainz, Germany. The complete electrode model is adapted for the given device to handle incomplete measurements and the inhomogeneities of the conductivity are a priori assumed to be sparse with respect to a certain basis. This prior information is incorporated into a Tikhonov-type functional by including a sparsity-promoting l1-regularization term. The functional is minimized with an iterative soft shrinkage-type algorithm.

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Authors

Gehre, M
Kluth, T
Sebu, C
Maass, P

Oxford Brookes departments

Faculty of Technology, Design and Environment\Department of Mechanical Engineering and Mathematical Sciences

Dates

Year of publication: 2014
Date of RADAR deposit: 2016-02-17


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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