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  • Classical electrical impedance tomography (EIT) is an imaging modality in which the internal volume impedivity distribution is reconstructed based on the known injected currents and measured voltages on the surface of the object. Image reconstruction is an ill-posed inverse problem of finding such internal impedivity distribution that minimizes certain optimization criteria. The optimization necessitates algorithms that impose regularization and some prior information constraint. The regularization techniques vary in their complexity. This paper proposes the specification of significant parameters of regularization techniques such as the Tikhonov regularization method. We intend to show in the proposed paper the influence of these parameters on the stability, accuracy and convergence of an optimization process. The optimal parameters were found and applied during the image reconstruction process for a two-dimensional (2D) example. The obtained results were presented in related research reports.
  • Classical electrical impedance tomography (EIT) is an imaging modality in which the internal volume impedivity distribution is reconstructed based on the known injected currents and measured voltages on the surface of the object. Image reconstruction is an ill-posed inverse problem of finding such internal impedivity distribution that minimizes certain optimization criteria. The optimization necessitates algorithms that impose regularization and some prior information constraint. The regularization techniques vary in their complexity. This paper proposes the specification of significant parameters of regularization techniques such as the Tikhonov regularization method. We intend to show in the proposed paper the influence of these parameters on the stability, accuracy and convergence of an optimization process. The optimal parameters were found and applied during the image reconstruction process for a two-dimensional (2D) example. The obtained results were presented in related research reports. (en)
Title
  • Significant Parameters of Image Reconstruction Convergence
  • Significant Parameters of Image Reconstruction Convergence (en)
skos:prefLabel
  • Significant Parameters of Image Reconstruction Convergence
  • Significant Parameters of Image Reconstruction Convergence (en)
skos:notation
  • RIV/00216305:26220/10:PU87043!RIV11-MSM-26220___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM0021630503)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 287268
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26220/10:PU87043
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • image processing, EIT (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [409DE35888FB]
http://linked.open...v/mistoKonaniAkce
  • Žilina
http://linked.open...i/riv/mistoVydani
  • Neuveden
http://linked.open...i/riv/nazevZdroje
  • ELEKTRO 2010 proceedings
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Ostanina, Ksenia
  • Dědková, Jarmila
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • Neuveden
https://schema.org/isbn
  • 978-80-554-0196-6
http://localhost/t...ganizacniJednotka
  • 26220
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