Measurement Image Reconstruction in Electrical Impedance Tomography through 1D-UNet
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0198064" target="_blank" >RIV/00216305:26220/26:0198064 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.23919/MEASUREMENT66999.2025.11078744" target="_blank" >http://dx.doi.org/10.23919/MEASUREMENT66999.2025.11078744</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/MEASUREMENT66999.2025.11078744" target="_blank" >10.23919/MEASUREMENT66999.2025.11078744</a>
Alternative languages
Result language
angličtina
Original language name
Measurement Image Reconstruction in Electrical Impedance Tomography through 1D-UNet
Original language description
This paper presents a deep learning approach for image reconstruction in Electrical Impedance Tomography using a one-dimensional U-Net model. The model’s performance is evaluated against traditional methods such as the Total Variation and Gauss-Newton algorithms. Experimental results demonstrate that 1D-UNet consistently achieves superior reconstruction accuracy, particularly in noisy environments. In noise-free conditions, the model attains higher correlation coefficients and structural similarity values than conventional approaches, preserving fine details effectively. Under noisy conditions (30 dB and 60 dB), 1D-UNet maintains a significantly higher correlation and structural similarity, demonstrating its robustness. The strong generalization and adaptability of the proposed method underscore its potential for enhancing tomographic imaging applications in biomedical diagnostics, industrial process monitoring.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20201 - Electrical and electronic engineering
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 15th International Conference on Measurement
ISBN
978-80-69159-00-6
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
2-5
Publisher name
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Place of publication
Smolenice
Event location
Smolenice
Event date
Jun 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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