Detail publikace

Image Reconstruction in Electrical Impedance Tomography through Multilayer Perceptron

KOUAKOUO NOMVUSSI, S. MIKULKA, J.

Originální název

Image Reconstruction in Electrical Impedance Tomography through Multilayer Perceptron

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

This study introduces a novel image reconstruction algorithm designed to excel in challenging scenarios with noisy datasets. Comparative evaluations against established methods, the Total Variation technique and the Gauss-Newton algorithm, are conducted using key performance metrics including the correlation coefficient and structural similarity index. The Results demonstrate that the proposed algorithm displays variable performance in noise-free data compared to Total Variation but consistently outperforms it in the presence of noise. Furthermore, when contrasted with the Gauss-Newton algorithm, the proposed method consistently exhibits superior outcomes, particularly in scenarios involving noisy datasets, where the Gauss-Newton algorithm faces limitations. This study underscores the robustness of the proposed algorithm in noisy conditions, suggesting its potential for applications where accurate image reconstruction is critical.

Klíčová slova

Multilayer Perceptron, Total Variation, Newton-Gauss, EIT.

Autoři

KOUAKOUO NOMVUSSI, S.; MIKULKA, J.

Vydáno

23. 4. 2024

Nakladatel

VUT v Brně

Místo

Brno

ISBN

978-80-214-6231-1

Kniha

Proceedings I of the 30th Conference STUDENT EEICT 2024

Strany od

303

Strany do

307

Strany počet

5

URL

https://www.eeict.cz/download

BibTex

@inproceedings{BUT188847,
  author="Serge Ayme {Kouakouo Nomvussi} and Jan {Mikulka}",
  title="Image Reconstruction in Electrical Impedance Tomography through Multilayer Perceptron",
  booktitle="Proceedings I of the 30th Conference STUDENT EEICT 2024",
  year="2024",
  pages="303--307",
  publisher="VUT v Brně",
  address="Brno",
  isbn="978-80-214-6231-1",
  url="https://www.eeict.cz/download"
}