Detail publikace

Domain Shape Optimization in Electrical Impedance Tomography

MIKULKA, J. DUŠEK, J. CHALUPA, D.

Originální název

Domain Shape Optimization in Electrical Impedance Tomography

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper introduces the optimization of domain shape parameters in electrical impedance tomography-based imaging. Precise impedance reconstruction requires accurate, well-correlated physical and numerical finite element method (FEM) models; thus, we employed the Nelder-Mead algorithm and a complete electrode model to evaluate the domain shape deformation. The deformation of the originally circular model is defined by the size of the major and minor axes of the equivalent elliptical shape. The optimization process was designed to calculate the parameters of the numerical model before the image reconstruction begins. The models were verified via simulation and experimental measurement with adjacent strategy. The optimized model reduced the overall conductivity distribution error of 6.16%. The designed optimization process proved to be suitable for correlating the numerical and the physical models, and it also enabled us to effectively eliminate imaging uncertainties and artifacts.

Klíčová slova

Electrodes, Electrical impedance tomography, Uncertainty, Random access memory, Conductivity, Nonhomogeneous media, Numerical models

Autoři

MIKULKA, J.; DUŠEK, J.; CHALUPA, D.

Vydáno

21. 11. 2021

ISBN

978-1-7281-7247-7

Kniha

Photonics & Electromagnetics Research Symposium (PIERS)

ISSN

1559-9450

Periodikum

Progress In Electromagnetics

Stát

Spojené státy americké

Strany od

2155

Strany do

2159

Strany počet

5

BibTex

@inproceedings{BUT177477,
  author="Jan {Mikulka} and Jan {Dušek} and Daniel {Chalupa}",
  title="Domain Shape Optimization in Electrical Impedance Tomography
",
  booktitle="Photonics & Electromagnetics Research Symposium (PIERS)",
  year="2021",
  journal="Progress In Electromagnetics",
  pages="2155--2159",
  doi="10.1109/PIERS53385.2021.9694687",
  isbn="978-1-7281-7247-7",
  issn="1559-9450"
}