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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JB - Sensors, detecting elements, measurement and regulation

  • OECD FORD branch

Result continuities

  • Project

  • 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

  • e-ISSN

  • 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