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Matematicheskoe modelirovanie, 2012, Volume 24, Number 5, Pages 65–80 (Mi mm3250)  

This article is cited in 1 scientific paper (total in 1 paper)

Development of block ñycling inversion method in computer tomography

A. V. Khovanskiy

TRINITI, Troitsk
Full-text PDF (698 kB) Citations (1)
References:
Abstract: The development of block-cycling Radon inversion method (BCI) [1] in computer tomography for spiral-fan scheme of scanning (SFSS) and cylinder inspection domain is presented. 3-dim inverse Radon problem is reduced to series of $P$ 2-dim inverse Radon problems with the same Radon matrix. Taking into account a priori information about circle invariability for fan scheme of scanning (FSS) allows to apply direct block-cycling inversion of 2-dim Radon matrix by block-Greville-1 method instead of a classical block-teoplitz inversion (BTI) [2,3] based on the notion of teoplitz rang. The time complexity of the BCI algorithm $N$ times better by performance at the stage of the preliminary inversion, so as on the flow due to the vectotization. Memory volume required is also 6 times better. But it’s main advantage — the simplicity of implementation due to the absence of main minor degeneration problem. The BCI algorithm was numerically simulated with the space resolution up to $201\times201$ (with – 2 sec. on the flow with 20 sec. for preliminary inversion of Radon matrix with spatial resolution $101\times101$ at the PC PENTIUM–4, Visual Fortran 90). Stability coefficient $\sim 10$, 75(in metric $\mathrm{L}_2$, $\mathrm{C}$) — 3–10 times better comparing with result in [23] due to the filtration of noise in Radon projection, smoothing of the solution and some other improvements. Singularity problem mentioned in [1] is also solved. The results obtained in this work may be applied for fourth generation tomography soft ware.
Keywords: (accuracy, complexity, parallel processing, stability) of algorithm, computer tomography (FFT(Fast Fourier Transform), BCI(Block Cycling Inversion), BTI(Block Teoplitz Inversion), GB(Glassman-de Boor), G(Greville), NN(Neuron Nets), BP(Back Projection), LS(Least Square) and others) methods, Radon(equation, image, matrix, operator, problem, projection), (Wedderburn, Gauss–Markoff, convolution) theorem, (fan-spyral, parallel) Scheme of Scanning.
Received: 20.06.2011
English version:
Mathematical Models and Computer Simulations, 2012, Volume 4, Issue 6, Pages 611–621
DOI: https://doi.org/10.1134/S2070048212060075
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. V. Khovanskiy, “Development of block ñycling inversion method in computer tomography”, Matem. Mod., 24:5 (2012), 65–80; Math. Models Comput. Simul., 4:6 (2012), 611–621
Citation in format AMSBIB
\Bibitem{Kho12}
\by A.~V.~Khovanskiy
\paper Development of block ñycling inversion method in computer tomography
\jour Matem. Mod.
\yr 2012
\vol 24
\issue 5
\pages 65--80
\mathnet{http://mi.mathnet.ru/mm3250}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=3025819}
\elib{https://elibrary.ru/item.asp?id=21276758}
\transl
\jour Math. Models Comput. Simul.
\yr 2012
\vol 4
\issue 6
\pages 611--621
\crossref{https://doi.org/10.1134/S2070048212060075}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-84929083444}
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  • https://www.mathnet.ru/eng/mm/v24/i5/p65
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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    Abstract page:417
    Full-text PDF :129
    References:62
    First page:11
     
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