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Computer Optics, 2020, Volume 44, Issue 2, Pages 250–258
DOI: https://doi.org/10.18287/2412-6179-CO-691
(Mi co787)
 

This article is cited in 8 scientific papers (total in 8 papers)

IMAGE PROCESSING, PATTERN RECOGNITION

Method for selection macular edema region using optical coherence tomography data

N. Yu. Ilyasovaab, N. S. Deminba, A. S. Shirokanevab, A. V. Kupriyanovab, E. A. Zamytskiyc

a Samara National Research University, Moskovskoye Shosse 34, 443086, Samara, Russia
b IPSI RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Molodogvardeyskaya 151, 443001, Samara, Russia
c Samara Regional Clinical Ophthalmological Hospital named after T.I. Eroshevsky, Samara, Russia
References:
Abstract: The paper proposes a method for selection the region of diabetic macular edema in fundus images using OCT data. The relevance of the work is due to the need to create support systems for laser coagulation to increase its effectiveness. The proposed algorithm is based on a set of image segmentation methods, as well as searching for specific points and compiling their descriptors. The Canny method is used to find the boundary between the vitreous body and the retina in OCT images. The segmentation method, based on the Kruskal algorithm for constructing the minimum spanning tree of a weighted connected undirected graph, is used to select the retina to the pigment layer in the image. Using the results of segmentation, a map of the thickness of the retina of the eye and its deviation from the norm were constructed. In the course of the research, the optimal parameter values were selected in the Canny and graph segmentation algorithms, which allow to achieve a segmentation error of 5 %. SIFT, SURF, and AKAZE methods were considered for super-imposing calculated maps of the retina thickness and its deviation from the norm on the fundus image. In cases where a picture from the fundus camera of the OCT apparatus is provided along with OCT data, using the SURF method, it is possible to accurately combine with the fundus image.
Keywords: laser coagulation, eye fundus, diabetic retinopathy, OCT images, graph-based image segmentation, SIFT, SURF descriptors.
Funding agency Grant number
Russian Foundation for Basic Research 19-29-01135 ìê
19-31-90160 ìîë_à
Ministry of Science and Higher Education of the Russian Federation
This work was financially supported by the Russian Foundation for Basic Research under grant # 19-29-01135, # ¹ 19-31-90160 and by the Ministry of Science and Higher Education within the State assignment to the FSRC “Crystallography and Photonics” RAS.
Received: 07.01.2020
Accepted: 07.02.2020
Document Type: Article
Language: Russian
Citation: N. Yu. Ilyasova, N. S. Demin, A. S. Shirokanev, A. V. Kupriyanov, E. A. Zamytskiy, “Method for selection macular edema region using optical coherence tomography data”, Computer Optics, 44:2 (2020), 250–258
Citation in format AMSBIB
\Bibitem{IlyDemShi20}
\by N.~Yu.~Ilyasova, N.~S.~Demin, A.~S.~Shirokanev, A.~V.~Kupriyanov, E.~A.~Zamytskiy
\paper Method for selection macular edema region using optical coherence tomography data
\jour Computer Optics
\yr 2020
\vol 44
\issue 2
\pages 250--258
\mathnet{http://mi.mathnet.ru/co787}
\crossref{https://doi.org/10.18287/2412-6179-CO-691}
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  • https://www.mathnet.ru/eng/co787
  • https://www.mathnet.ru/eng/co/v44/i2/p250
  • This publication is cited in the following 8 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Computer Optics
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    References:19
     
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