Electrical impedance distribution in human torax: A modeling framework
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241772" target="_blank" >RIV/61989100:27240/18:10241772 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-68321-8_53" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-68321-8_53</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-68321-8_53" target="_blank" >10.1007/978-3-319-68321-8_53</a>
Alternative languages
Result language
angličtina
Original language name
Electrical impedance distribution in human torax: A modeling framework
Original language description
Electrical impedance tomography (EIT) is an imaging system suitable for long-term monitoring. To extend current uses of EIT, improvements in the image reconstruction algorithms are essential. New image reconstruction methods for EIT can be tested on an impedance model of human body. Moreover, accurate anatomical impedance distribution models of human body are used to generate training data used in machine learning algorithms. Simulation framework, introduced in this paper, is capable of autonomous conversion of Computed tomography (CT) scans from DICOM format into 2D MESH human thorax impedance distribution model. Developed impedance models of large thorax structures achieve accurate results through segmentation of CT images and Fourier Fitting. Framework is developed in MATLAB as an extension to EIDORS and NETGEN frameworks. (C) Springer International Publishing AG 2018.
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
20202 - Communication engineering and systems
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 679
ISBN
978-3-319-68320-1
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
8
Pages from-to
512-519
Publisher name
Springer
Place of publication
Cham
Event location
Varna
Event date
Sep 14, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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