2003Dianzi xuebaoRequires access

New Method to Reconstruct Static Image in Electrical Impedance Tomography

MO Yulong

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Abstract

Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed,non-linear inverse problem.Especially in static EIT,the modified Newton-Raphson (MNR) reconstruction algorithm with regularization technique based on minimizing the object function is usually not stable,even divergent,due to the serious image reconstruction model error and measurement noise.A new static image reconstruction method for EIT based on genetic algorithm (GA-EIT) is proposed in this paper,in which the global optimized solution for EIT problem will be converged by evolution without need of regularization.The experimental results also indicate that the performance (including the precision and space resolution in reconstructing the static EIT image) of the GA-EIT algorithm is better than that of the MNR algorithm.

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What this paper is about

Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed,non-linear inverse problem.Especially in static EIT,the modified Newton-Raphson (MNR) reconstruction algorithm with regularization technique based on minimizing the object function is usually not stable,even divergent,due to the serious image reconstruction model error and measurement noise.A new static image reconstruction method for EIT based on genetic algorithm (GA-EIT) is proposed in this paper,in which the global optimized solution for EIT problem will be converged by evolution without need of regularization.The experimental results also indicate that the performance (including the precision and space resolution in reconstructing the static EIT image) of the GA-EIT algorithm is better than that of the MNR algorithm.

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Available abstract

Image reconstruction in electrical impedance tomography (EIT) is a highly ill-posed,non-linear inverse problem.Especially in static EIT,the modified Newton-Raphson (MNR) reconstruction algorithm with regularization technique based on minimizing the object function is usually not stable,even divergent,due to the serious image reconstruction model error and measurement noise.A new static image reconstruction method for EIT based on genetic algorithm (GA-EIT) is proposed in this paper,in which the global optimized solution for EIT problem will be converged by evolution without need of regularization.The experimental results also indicate that the performance (including the precision and space resolution in reconstructing the static EIT image) of the GA-EIT algorithm is better than that of the MNR algorithm.

Key concepts: Electrical impedance tomography, Iterative reconstruction, Regularization (linguistics), Inverse problem, Algorithm, Tomography, Image resolution, Mathematics

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