informИнформатикаInformatics1816-03012617-6963UIIP NASBinform-319Research ArticleОБРАБОТКА СИГНАЛОВ, ИЗОБРАЖЕНИЙ, РЕЧИ И ТЕКСТАSIGNAL, IMAGE, SPEECH AND TEXT PROCESSINGАЛГОРИТМ ОПРЕДЕЛЕНИЯ ХАРАКТЕРИСТИК КРОВОТОКА В СОСУДАХ ГЛАЗНОГО ДНА ПО ВИДЕОПОСЛЕДОВАТЕЛЬНОСТИTHE ALGORITHM OF DETERMINATION OF EYE FUNDUS VESSELS BLOOD FLOW CHARACTERISTICS ON VIDEOSEQUENCEНедзьведьО. В.NedzvedzO. V.

старший преподаватель кафедры медицинской и биологической физики

Senior Lecturer at the Department of Medical and Biological Physics

olga_nedzved@tut.byАбламейкоС. В.AblameykoS. V.

доктор технических наук, академик НАН Беларуси, профессор механико-математического факультета

D. Sc. (Technical Sciences), Academician of the National Academy of Science of Belarus, Professor at the Faculty of Mathematics and Mechanics

ablameyko@bsu.byНедзьведьА. М.NedzvedA. M.

доктор технических наук, заведующий кафедрой компьютерных технологий и систем

D. Sc. (Technical Sciences), Head of Department of Computer Technologies and Systems

nedzveda@tut.byГлинскийА. В.GlinskyA. V.

научный сотрудник лаборатории информационно-компьютерных технологий

Researcher at the Laboratory of Computing Technologies

glinskyav@bsmu.byКарапетянГ. М.KarapetyanG. M.

заведующий лабораторией информационно-компьютерных технологий

Head of the Laboratory of Computing Technologies

greg@itlab.anitex.byАнисимовА. А.AnisimovA. A.

ассистент кафедры нормальной анатомии

Assistant of the Department of Normal Physiology

anisimovaa@bsmu.byГуревичИ. Б.GurevichI. B.

кандидат физико- математических наук, заведующий отделом математических и прикладных методов анализа изображений и нелинейных задач

Ph. D. (Physics and Mathematics), Head of Department of Mathematical Pattern Recognition and Methods of Combinatorial Analysis

igourevi@ccas.ruЯшинаВ. В.YashinaV. V.

кандидат физико-математических наук, ведущий научный сотрудник

Ph. D. (Physics and Mathematics), Leading Research Scientist at the Department of Mathematical Pattern Recognition and Methods of Combinatorial Analysis

werayashina@gmail.comБелорусский государственный университет, Минск; Объединенный институт проблем информатики Национальной академии наук Беларуси, МинскBelarusian State University, Minsk; The United Institute of Informatics Problems of the National Academy of Sciences of Belarus, MinskБелорусский государственный университет, МинскBelarusian State University, MinskБелорусский государственный медицинский университет, МинскBelarusian State Medical University MinskФедеральный исследовательский центр «Информатика и управление» Российской академии наук (Вычислительный центр им. А. А. Дородницына), МоскваFederal Research Center "Informatics and Management" of the Russian Academy of Sciences (Dorodnitsyn Computing Center), Moscow20182603201815192102Copyright © Недзьведь О.В., Абламейко С.В., Недзьведь А.М., Глинский А.В., Карапетян Г.М., Анисимов А.А., Гуревич И.Б., Яшина В.В., 20182018Недзьведь О.В., Абламейко С.В., Недзьведь А.М., Глинский А.В., Карапетян Г.М., Анисимов А.А., Гуревич И.Б., Яшина В.В.Nedzvedz O.V., Ablameyko S.V., Nedzved A.M., Glinsky A.V., Karapetyan G.M., Anisimov A.A., Gurevich I.B., Yashina V.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://inf.grid.by/jour/article/view/319

Рассматривается метод определения динамических количественных характеристик кровотока в сосудах глазного дна глаза, таких как изменение диаметра сосуда, линейная и объемная скорости кровотока. Данные характеристики позволяют определить изменения кровотока в микроциркуляторном русле, влияющие на кровоток в сосудах мозга, почек и коронарных сосудах. Разработанный алгоритм включает этапы стабилизации видеопоследовательности, сегментации сосудов с помощью нейронной сети, определения мгновенной скорости в сосуде на основе оптического потока, анализа полученных результатов.

 

The method of determination of the dynamic characteristics like the vessel diameter change, the linear and volume blood velocities in the vessels of the eye fundus is considered. Such characteristics allow to determine blood flow changes in the microvasculature affecting the blood flow in the brain, kidneys and coronary vessels. Developed algorithm includes four stages: the video sequence stabilization, the vessels segmentation with the help of a neural network, the determination of the instantaneous velocity in the vessels based on the optical flow and the analysis of the results.

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The authors declare that there are no conflicts of interest present.