Image reconstruction in electrical impedance tomography using neural network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096789" target="_blank" >RIV/61989100:27240/15:86096789 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CIBEC.2014.7020959" target="_blank" >http://dx.doi.org/10.1109/CIBEC.2014.7020959</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CIBEC.2014.7020959" target="_blank" >10.1109/CIBEC.2014.7020959</a>
Alternative languages
Result language
angličtina
Original language name
Image reconstruction in electrical impedance tomography using neural network
Original language description
Electrical impedance tomography (EIT) imaging method is gaining its popularity due to ease of use and also non-invasiveness. The inner distribution of resistivity, which corresponds to different resistivity properties of different tissues, is estimated from voltage potentials measured on the boundary of inspected object. The major problem of EIT is how to reconstruct the image of inner resistivity. There are many approaches to solve this issue, which require more computational demands. The use of neuralnetwork to solve this non-linear problem addresses the demand to ease the implementation and lower the computational demands. In this article we adopted the use of Radial Basis Function (RBF) neural network for image reconstruction and compared it to reconstructed images obtained using EIDORS software. RBF network was created and trained using the Matlab and neural network toolbox. As training data the simulated measurement voltages and EIDORS difference reconstruction gained values of
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JB - Sensors, detecting elements, measurement and regulation
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
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 7th Cairo International Biomedical Engineering Conference, CIBEC 2014
ISBN
978-1-4799-4412-5
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
39-42
Publisher name
Institute of Electrical and Electronics Engineers
Place of publication
New York
Event location
Giza
Event date
Dec 11, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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