Conductivity Profile Reconstruction of Stroke Head Models Based on Divide-and-Conquer Method and the Genetic Algorithm

Charles T.M. Choi*, Chieh Cheng Yu, Yan Hung Lai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This article used finite element (FE) analysis to study and analyze the electrical conductivity profile of simulated stroke patients based on a 45 dB signal-to-noise ratio synthesized measurement. Clinical measurement data obtained from stroke patients with electrical impedance tomography (EIT) was reported to be approximately 45 dB SNR. Weighting factors in conjunction with the divide-and-conquer method and adaptive genetic algorithm (AGA) were used. The AGA was applied with the weighting factors to identify the conductivity distribution inside the brain by minimizing the difference between the simulation and synthesized measured voltages under stroke conditions. The result shows that it might be possible to reconstruct an approximate electrical conductivity distribution based on 45 dB SNR simulated measurement of stroke data.

Original languageEnglish
Article number5000104
Pages (from-to)1-4
Number of pages4
JournalIEEE Transactions on Magnetics
Volume60
Issue number3
DOIs
StatePublished - 1 Mar 2024

Keywords

  • Conductivity distribution
  • finite element (FE) analysis
  • genetic algorithm (GA)
  • optimization
  • stroke

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