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Stochastic Optimization Approaches to Image Reconstruction in Electrical Impedance Tomography

  • Chang-Jin Boo
  • Ho-Chan Kim
  • Min-Jae Kang
  • Kwang Y. Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6017)

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.

Keywords

Particle Swarm Optimization Particle Swarm Optimization Algorithm Electrical Impedance Tomography Resistivity Distribution Simultaneous Perturbation Stochastic Approximation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Chang-Jin Boo
    • 1
  • Ho-Chan Kim
    • 1
  • Min-Jae Kang
    • 1
  • Kwang Y. Lee
    • 2
  1. 1.Department of Electrical EngineeringJeju National UniversityKorea
  2. 2.Department of Electrical and Computer EngineeringBaylor UniversityUSA

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