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OSTANINA, K. DĚDKOVÁ, J.
Original Title
Significant Parameters of Image Reconstruction Convergence
Type
conference paper
Language
English
Original Abstract
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.
Keywords
image processing, EIT
Authors
OSTANINA, K.; DĚDKOVÁ, J.
RIV year
2010
Released
24. 5. 2010
ISBN
978-80-554-0196-6
Book
ELEKTRO 2010 proceedings
Pages from
41
Pages to
44
Pages count
4
BibTex
@inproceedings{BUT29160, author="Ksenia {Kořínková} and Jarmila {Dědková}", title="Significant Parameters of Image Reconstruction Convergence", booktitle="ELEKTRO 2010 proceedings", year="2010", pages="41--44", isbn="978-80-554-0196-6" }