Stochastic optimization approaches to image reconstruction in electrical impedance tomography

  • Authors:

  • Chang-Jin Boo;Ho-Chan Kim;Min-Jae Kang;Kwang Y. Lee

  • Affiliations:

  • Department of Electrical Engineering, Jeju National University, Korea;Department of Electrical Engineering, Jeju National University, Korea;Department of Electrical Engineering, Jeju National University, Korea;Department of Electrical and Computer Engineering, Baylor University

  • Venue:
  • ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part II
  • Year:
  • 2010

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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 two stochastic optimization techniques such as particle swarm optimization (PSO).and simultaneous perturbation stochastic approximation (SPSA) algorithms for solving the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, particle swarm optimization, and simultaneous perturbation stochastic approximation.