The Transactions of the Korean Institute of Electrical Engineers D (대한전기학회논문지:시스템및제어부문D)

The Korean Institute of Electrical Engineers (대한전기학회)
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A Image Reconstruction Uing Simulated Annealing in Electrical Impedance Tomograghy

시뮬레이티드 어닐링을 이용한 전기임픽던스단층촬영법의 영상복원

  • 김호찬 (제주대 공대 전기전자공학부) ;
  • 부창진 (제주대 공대 전기전자공학부) ;
  • 이윤준 (제주대 공대 에너지공학과)
  • Published : 2003.02.01
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Abstract

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reconstruction algorithm for the solution of the static EIT inverse problem. Computer simulations with the 32 channels synthetic data show that the spatial resolution of reconstructed images by the proposed scheme is improved as compared to that of the mNR algorithm or genetic algorithm at the expense of increased computational burden.

Keywords

References

  1. J. G. Webster, Electrical Impedance Tomography, Adam Hilger, , 1990
  2. T. J. Yorkey, J. G. Webster, and W. J. Tompskins, 'Comparing reconstruction algorithms for electrical impedance tomography', IEEE Trans. Biomed. Eng., Vol. BME-34, pp. 843-852, 1987 https://doi.org/10.1109/TBME.1987.326032
  3. M. Vauhkonen, Electrical Impedance Tomography and Priori Information, Natural and Environmental Sciences, Kuopio University Publications Co., 62, 1997
  4. M. C. Kim, S. Kim, K. Y. Kim, J. H. Lee, and Y. J. Lee, 'Reconstruction of particle concentration distribution in annular Couette flow using electrical impedance tomography,' J. Ind. Eng. Chem., vol. 7, no. 5, pp. 341-347, 2001
  5. R. Olmi, M. Bini, and S. Priori, 'A genetic algorithm approach to image reconstruction in electrical impedance tomography,' IEEE Trans. Evolutiomary Computation, vol. 4, no. 1, pp. 83-88, 2000 https://doi.org/10.1109/4235.843497
  6. S. Kirkpatrick, C. D. Gelatto, and M. P. Vecchi, 'Optimization by simulated annealing', Science, vol. 220, pp. 671-680, 1983 https://doi.org/10.1126/science.220.4598.671
  7. K. H. Cho, S. Kim, Y. J. Lee, 'Impedance imaging of two-phase flow field with mesh grouping method', Nuclear Engineering and Design, vol. 204, pp. 57-67, 2001 https://doi.org/10.1016/S0029-5493(00)00320-4