title: Ð¡ÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ°Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ ÐºÐ°Ð¿Ð¸Ð»Ð»ÑÑÐ½ÑÑ ÑÐ¾ÑÑÐ´Ð¾Ð² Ð³Ð»Ð°Ð·Ð° Ð¿Ð¾ ÑÐ½Ð¸Ð¼ÐºÐ°Ð¼ ÑÐµÐ»ÐµÐ²Ð¾Ð¹ Ð¾ÑÑÐ°Ð»ÑÐ¼Ð¾Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¾Ð¹ Ð»Ð°Ð¼Ð¿Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Semantic segmentation of capillary vessels eyes from the images of a slit ophthalmic lamp
Creators: name: ÐÐ°ÑÐ¸Ð½, ÐÐ³Ð¾Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ°Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ñ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
semantic segmentation
neural networks
computer vision
machine learning
artificial intelligence

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description: This paper describes the essence of the approach to creating a method of semantic segmentation of the capillary vessels of the eye based on the images of an ophthalmological slit lamp based on the use of a convolutional neural network. The analysis of existing solutions for segmentation of the vessels of the eye according to the available open data set is carried out. The analysis of images obtained with the help of an ophthalmological slit lamp was carried out. A method for evaluating and filtering marked-up data is proposed to solve the problem of the presence of poor-quality markup in the data. A neural network model was built and trained to solve the problem for a data set that differs in its content from publicly available data sets with which most studies were conducted. This method highlights more than 75% of the vessels in the eye image. This allows for a semi-automatic analysis of the state of the patient's cardiovascular system.