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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" }