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Algorithm for segmentation of visual signs of diabetic retinopathy (DR) and diabetic macular edema (DME) in digital fundus images

Number №4, 2021 - page 17-26
DOI: 10.29188/2712-9217-2021-7-4-17-26
For citation: Katalevskaya E.A., Katalevsky D.Yu., Tyurikov M.I., Shaykhutdinova E.F., Sizov A.Yu. Algorithm for segmentation of visual signs of diabetic retinopathy (DR) and diabetic macular edema (DME) in digital fundus images. Russian Journal of Telemedicine and E-Health 2021;7(4)17-26; https://doi.org/10.29188/2712-9217-2021-7-4-17-26
Katalevskaya E.A., Katalevskiy D.Yu., Tyurikov M.I., Shayhutdinova E.F., Sizov A.Yu.
Information about authors:

Katalevskaya E.A. – PhD, ophthalmologist, Scientific Director of RETINA AI project, Digital Vision Solutions LLC; Moscow, Russia
Katalevsky D.Y. – Ph.D., General Director, Digital Vision Solutions LLC; Moscow, Russia
Tyurikov M.I. – chief Software Engineer, Digital Vision Solutions LLC; Moscow, Russia
Shaykhutdinova E.F. – ophthalmologist of RETINA AI project, Digital Vision Solutions LLC; Moscow, Russia
Sizov A.Yu. – Software Engineer, Digital Vision Solutions LLC; Moscow, Russia

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This article is devoted to the development of an algorithm for segmentation of visual signs of DR and DMO. The paper references the global statistics of patients with diabetes mellitus and their need for regular fundus screening. We propose the use of telemedicine applications to the problem of regular ophthalmological screening of patients with diabetis mellitus. The main features of DR and DME are identified with the help of artificial intelligence algorithms. A list of scientific and technical problems that needed to be solved is presented: the collection of training data, their markup and the choice of artificial neural network architectures for the tasks of feature segmentation. The process of validation of the algorithm is described and the current results are presented.

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Keywords: diabetic retinopathy; diabetic macular edema; artificial neural networks; medical decision-making assistance system; segmentation