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Computer Research and Modeling, 2010, Volume 2, Issue 2, Pages 189–197
DOI: https://doi.org/10.20537/2076-7633-2010-2-2-189-197
(Mi crm594)
 

ANALYSIS AND MODELING OF COMPLEX LIVING SYSTEMS

A new biometric approach and efficient system for automatic detection and analysis of digital retinal images

L. A. Shulgaa, S. V. Saakyanb, D. A. Skladnevc

a Applied Acoustics Research Institute, 7a, 9 May st., 141981, Dubna, Moscow region, Russia
b Helmholtz Moscow Research Institute of Eye Diseases, 14/19, Sadovaya-Chernogryazskaya st., 105062 Moscow, Russia
c Research Institute for Genetics and Selection of Industrial Microorganisms, 1, 1-st Dorozhniy pr., 117545, Moscow, Russia
References:
Abstract: The program for automatic revealing of threshold values for characterizing physiological state of vessels and detection of early stages of retina pathology is offered. The algorithm is based on checking character of crossing sites of vessel images with the “mask” consisting of concentric circumferences (the first circumference is imposed directly on the sclera capsules of an optic nerve disk). The new method allows revealing of a network of blood vessels and flanking zones and detection of initial stage of pathological changes in a retina by digital images.
Keywords: Digital retina image, automatic image analysis, early stages of retina pathology.
Funding agency Grant number
Russian Foundation for Basic Research 08-07-00276
Received: 09.04.2010
Document Type: Article
UDC: 617.7, 004.93
Language: Russian
Citation: L. A. Shulga, S. V. Saakyan, D. A. Skladnev, “A new biometric approach and efficient system for automatic detection and analysis of digital retinal images”, Computer Research and Modeling, 2:2 (2010), 189–197
Citation in format AMSBIB
\Bibitem{ShuSaaSkl10}
\by L.~A.~Shulga, S.~V.~Saakyan, D.~A.~Skladnev
\paper A new biometric approach and efficient system for automatic detection and analysis of digital retinal images
\jour Computer Research and Modeling
\yr 2010
\vol 2
\issue 2
\pages 189--197
\mathnet{http://mi.mathnet.ru/crm594}
\crossref{https://doi.org/10.20537/2076-7633-2010-2-2-189-197}
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