Linearized solution to electrical impedance tomography based on the Schur conjugate gradient method

Bo Zhao, Huaxiang Wang, Xiaoyan Chen, Xiaolei Shi, Wuqiang Yang

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution of an inhomogeneous medium, usually by injecting a current at the periphery of an object and measuring the resulting changes in voltage. The conjugate gradient (CG) method is one of the most popular methods applied for image reconstruction, although its convergence rate is low. In this paper, an advanced version of the CG method, i.e. the Schur conjugate gradient (Schur CG) method, is used to solve the inverse problem for EIT. The solution space is divided into two subspaces. The main part of the solution lies in the coarse subspace, which can be calculated directly and its corresponding correction term with a small norm can be solved in the Schur complement subspace. This paper discusses the strategies of choosing parameters. Simulation results using the Schur CG algorithm are presented and compared with the conventional CG algorithm. Experimental results obtained by the Schur CG algorithm are also presented, indicating that the Schur CG algorithm can reduce the computational time and improve the quality of image reconstruction with the selected parameters. © 2007 IOP Publishing Ltd.
    Original languageEnglish
    Pages (from-to)3373-3383
    Number of pages10
    JournalMeasurement Science and Technology
    Volume18
    Issue number11
    DOIs
    Publication statusPublished - 1 Nov 2007

    Keywords

    • Conjugate gradient method
    • Electrical impedance tomography (EIT)
    • Image reconstruction
    • Schur complement conjugate gradient method

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