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Computer Optics, 2017, Volume 41, Issue 1, Pages 103–109
DOI: https://doi.org/10.18287/2412-6179-2017-41-1-103-109 (Mi co363) 		 
This article is cited in 3 scientific papers (total in 3 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

A method for digital renal scintigram analysis based on brightness and geometric features

A. V. Gaidelab, A. G. Khramova, A. V. Kapishnikovc, A. V. Kolsanovc, Yu. S. Pyshkinac

a Samara National Research University, Samara, Russia
b Image Processing Systems Institute of the RAS - Branch of the FSRC "Crystallography and Photonics" RAS, Samara, Russia
c Samara State Medical University, Samara, Russia
Full-text PDF (616 kB) Citations (3)
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DOI: https://doi.org/10.18287/2412-6179-2017-41-1-103-109
URL: https://www.computeroptics.smr.ru/KO/Annot/KO41-1/410112.html
Abstract: We proposed a method of automated scintigram image processing enabling an objective evaluation of the renal parenchyma condition to be made based on scintigram brightness and geometric characteristics with threshold processing. We studied the method using a set of real radionuclide images of a renal transplant. The results of clinical studies confirm the effectiveness of the developed method. We obtained objective numerical values associated with thresholding the image from 40% to 80%, based on which one can form an independent assessment of the presence or absence of focal lesions in the renal parenchyma.
Keywords: image processing, pattern recognition, scintigraphy, kidney disease, transplantation.
Funding agency Grant number
Russian Foundation for Basic Research 14-07-97040-р_поволжье_а
16-41-630761-р_а
Ministry of Education and Science of the Russian Federation
Russian Academy of Sciences - Federal Agency for Scientific Organizations
The work was partially funded by the Russian Foundation of Basic Research (grants 14-07-97040-р_поволжье_а and 16-41-630761 р_а), the Russian Federation Ministry of Education and Science as part of Samara University's competitiveness enhancement program in 2013-2020 and the RAS basic research program "Bioinformatics, modern information technologies and mathematical methods in medicine".
Received: 24.10.2016
Accepted: 06.12.2016
Document Type: Article
Language: Russian
Citation: A. V. Gaidel, A. G. Khramov, A. V. Kapishnikov, A. V. Kolsanov, Yu. S. Pyshkina, “A method for digital renal scintigram analysis based on brightness and geometric features”, Computer Optics, 41:1 (2017), 103–109
Citation in format AMSBIB
\Bibitem{GaiKhrKap17}
\by A.~V.~Gaidel, A.~G.~Khramov, A.~V.~Kapishnikov, A.~V.~Kolsanov, Yu.~S.~Pyshkina
\paper A method for digital renal scintigram analysis based on brightness and geometric features
\jour Computer Optics
\yr 2017
\vol 41
\issue 1
\pages 103--109
\mathnet{http://mi.mathnet.ru/co363}
\crossref{https://doi.org/10.18287/2412-6179-2017-41-1-103-109}
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    • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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