Abstract
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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