Automation of flow analysis in scleral vessels based on descriptive-associative algorithms

Blood flow reflects the eye's health and is disrupted in many diseases. Many pathological processes take place at the cellular level like as microcirculation of blood in vessels, and the processing of medical images is a difficult recognition task. Existing techniques for measuring blood flow are limited due to the complex assumptions, equipment and calculations requirements. In this paper, we propose a method for determining the blood flow characteristics in eye conjunctiva vessels, such as linear and volumetric blood speed and topological characteristics of the vascular net. The method preprocesses the video to improve the conditions of analysis and then builds an integral optical flow for definition of flow dynamical characteristic of eye vessels. These characteristics make it possible to determine changes in blood flow in eye vessels. We show the efficiency of our method in natural eye vessel scenes. The research provides valuable insights to novices with limited experience in the diagnosis and can serve as a valuable tool for experienced medical professionals.