Publication detail

Training set generation system for reconstruction of electrical impedance tomography images

ZEMITI, S. ALOPH, C. MIKULKA, J.

Original Title

Training set generation system for reconstruction of electrical impedance tomography images

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper introduces an innovative approach to simulating Electrical Impedance Tomography (EIT) through MATLAB, aimed at advancing the accuracy and reliability of internal imaging using electrodes. We address the critical challenge of reconstructing interior images with high fidelity by simulating inhomogeneous mediums. Our methodology involves the generation of synthetic datasets, encompassing various inhomogeneity scenarios, followed by applying forward solutions to ascertain voltage measurements indicative of interior conductivity variations. The research emphasizes the creation of an adaptive framework capable of simulating real-world scenarios within a controlled digital environment, thereby enhancing the predictive capabilities of EIT systems in diverse applications ranging from medical imaging to industrial inspection.

Keywords

EIT, image reconstruction, dataset generation, forward problem, conductivity distribution, inhomogeneity mapping, MATLAB.

Authors

ZEMITI, S.; ALOPH, C.; MIKULKA, J.

Released

23. 4. 2024

Publisher

VUT v Brně

Location

Brno

ISBN

978-80-214-6231-1

Book

Proceedings I of the 30th Conference STUDENT EEICT 2024

Pages from

190

Pages to

193

Pages count

4

URL

https://www.eeict.cz/download

BibTex

@inproceedings{BUT188846,
  author="Samia {Zemiti} and Clark {Aloph} and Jan {Mikulka}",
  title="Training set generation system for reconstruction of electrical impedance tomography images",
  booktitle="Proceedings I of the 30th Conference STUDENT EEICT 2024",
  year="2024",
  pages="190--193",
  publisher="VUT v Brně",
  address="Brno",
  isbn="978-80-214-6231-1",
  url="https://www.eeict.cz/download"
}