Original title: Image Reconstruction in Electrical Impedance Tomography through Multilayer Perceptron
Authors: Kouakouo Nomvussi, Serge Ayme ; Mikulka, Jan
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: 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.
Keywords: EIT; Multilayer Perceptron; Newton- Gauss; Total Variation
Host item entry: Proceedings I of the 30st Conference STUDENT EEICT 2024: General papers, ISBN 978-80-214-6231-1, ISSN 2788-1334

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: https://hdl.handle.net/11012/249257

Permalink: http://www.nusl.cz/ntk/nusl-622493


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