An Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography

Hui Zhang; Li Wang; Yongjun Zhou; Peijie Zhang; Jixia Wu; Ying Li

doi:10.4236/ojbiphy.2013.34027

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Open Journal of Biophysics > Vol.3 No.4, October 2013

An Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography ()

Hui Zhang, Li Wang, Yongjun Zhou, Peijie Zhang, Jixia Wu, Ying Li

Department of Civil, Environmental and Geomatic Engineering, University College London, London, UK.
Faculty of Physics and Electronic Engineering, Xianyang Normal University, Xianyang, China.
School of Highway, Chang’an University, Xi’an, China.

DOI: 10.4236/ojbiphy.2013.34027 PDF HTML 3,052 Downloads 4,803 Views Citations

Abstract

Electrical impedance tomography (EIT) reconstructs the internal impedance distribution of the body from electrical measurements on body surface. The algorithm research is one of the main problems of the EIT. This paper presents the MPSO-MNR Algorithm, which is formed by combining the Modified Particle Swarm Optimization (MPSO) with Modified Newton-Raphson algorithm (MNR), gives the reconstruction results of certain configurations and analyzes the influence of the noise on the MPSO-MNR algorithm in the EIT. The numerical results show that the MPSO-MNR algorithm can reconstruct the resistivity distribution within the certain iterations. With the moving of the target to the centre of 2-D solution domain and the increase of noise, the border of the reconstruction objects becomes vague, and the fitness value and the total error increase gradually.

Keywords

MPSO-MNR Algorithm; Signal-To-Noise Ratio; Objective Function; EIT

Share and Cite:

Zhang, H. , Wang, L. , Zhou, Y. , Zhang, P. , Wu, J. and Li, Y. (2013) An Influence of the Noise on the Imaging Algorithm in the Electrical Impedance Tomography. Open Journal of Biophysics, 3, 217-221. doi: 10.4236/ojbiphy.2013.34027.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	H. Dehghani and M. Soleimani, “Numerical Modeling Errors in Electrical Impedance Tomography,” Physiological Measurement, Vol. 28, No. 7, 2007, pp. S45-S55. http://dx.doi.org/10.1088/0967-3334/28/7/S04
[2]	G.-Z. Xu, Y. Li, et al, “Electrical Impedance Tomography in Biomedical Engineering,” China Machine Press, Beijing, 2010.
[3]	W. He, C.-Y. Luo, Z. Xu, et al., “Principle of the Electrical Impedance Tomography,” Science Press, Beijing, 2009.
[4]	Y. Li, G. Z. Xu, L. Y. Rao, et al., “MNR Method with Self-Determined Regularization Parameters for Solving Inverse Resistivity Problem,” Proceedings of 27th Annual International Conference of the IEEE Engineering in Medicine and Biology, Vol. 3, 2005, pp. 2653-2655.
[5]	H. Zhang, Y.-J. Zhou and X.-D. Zhang, “Algorithm Study of 2-D Electrical Impedance Tomography,” Journal of Xianyang Normal University, Vol. 27, No. 2, 2012, pp. 17- 19.
[6]	H. Zhang, X.-D. Zhang, et al., “Electromagnetic Imaging of the 2-D Media Based on Particle Swarm Algorithm,” 2010 Sixth International Conference on Natural Computation (ICNC), 10-12 August 2010, pp. 262-264.
[7]	H. Zhang, H. B. Wang, Y. J. Zhou and X. D. Zhang, “Research of Electrical Impedance Tomography Based on the Modified Particle Swarm Optimization,” 2012 Eighth International Conference on Natural Computation (ICNC), 29-31 May 2012, pp. 1127-1129.
[8]	R. Olmi, M. Bini and S. Priori, “A Genetic Algorithm Approach to Image Reconstruction in Electrical Impedance Tomography,” IEEE Transactions on Evolutionary Computation, Vol. 4, No. 1, 2000, pp. 83-88. http://dx.doi.org/10.1109/4235.843497
[9]	H. Zhang, Y. Li, X. M. Wang and X. D. Zhang, “MPSO- MNR Algorithm Study of 2-D Electrical Impedance Tomography,” Computer Engineering and Applications, Vol. 49, No. 3, 2013, pp. 29-32.
[10]	M. Donelli and A. Massa, “Computational Approach Based on a Particle Swarm Optimizer for Microwave Imaging of Two-Dimensional Dielectric Scatterers,” IEEE Transactions on Microwave Theory and Techniques, Vol. 53, No. 5, 2005, pp. 1761-1776. http://dx.doi.org/10.1109/TMTT.2005.847068
[11]	S. Huang, “Regularization Algorithm Research of Static Electrical Impedance Tomography,” Ph.D. Dissertation, Chongqing University, Chongqing, 2005.