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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.

has been cited by the following article:

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

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

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

  JOURNAL NAME: Open Journal of Biophysics, Vol.3 No.4, October 17, 2013

  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.