Saratov JOURNAL of Medical and Scientific Research

Computer analysis of epiretinal membrane parameters

Year: 2017, volume 13 Issue: №2 Pages: 350-358
Heading: Ophtalmology Article type: Original article
Authors: Daurov S.K., Dolinina O.N., Kamenskikh T.G., Batischeva Yu.S., Kolbenev I.O., Andreychenko O.A., Potemkin S.A., Proskudin R.A.
Organization: Yuri Gagarin State Technical University of Saratov, Saratov State Medical University

Objective: to develop algorithms of processing of video images of optical slices of the eye retina to quantify the degree of folding of the epiretinal membranes and of the central fossa. Material and methods. The object of the study was the video image of the retina obtained by optical coherence tomography. To develop methods of determining the degree of folding epiretinal membrane was formed mathematical model of the profile consisting of a base profile (low frequency component) and folding (high frequency part). Results. There had been developed two alternative methods of estimation of folding epiretinal membrane: retinal-averaging method and the method using the wavelet transform. The algorithm of geometrical parameters of the central fossa: the height, width and line shape. These algorithms are implemented in a software system. Conclusion. The practical application of the developed system showed its adequacy, as well as an introduction into medical practice the use of quantitative estimates of some parameters of the retina condition.

1. Lambroso В, Rispolini M. ОСТ of retina: The method of analysis and interpretation. Moscow, 2012; 83 p.
2. Gonsales R., Woods R. Digital image processing. Moscow: Technosphera, 2005; 1072 p.
3. Daurov SK, Proskudin RA. The algorithm of quantitative assessment of the degree of deformation of the profile of the retina. Mathematical methods in technics and technologies 2016; 89 (7): 53-56
4. Poteomkin SA, Daurov SK. The search algorithm and determine the parameters of the central fovea of the retina. Mathematical methods in technics and technologies 2016. 89 (7): 50-52.

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