Development and Experimental Investigation of Mathematical Methods for Automating the Diagnostics and Analysis of Ophthalmological Images

AI image-based diagnosis systems: how to implement them?

“…Russian-Belarusian system for analysis of ophthalmology images has been developed to solve the following tasks: (1) identification of the lipid layer state in the intermarginal space of human eyelids; (2) analysis of the degree of cellular structure density (cellularity) in the corneal tissue of human eyes; (3) identification of the state of the retinal blood flow when analyzing fluorescent angiograms of the human fundus; and (4) morphometric analysis of the state of the epithelium posterius (endothelium) in the human eye cornea. For each task, the following results were obtained: (1) expectations and variances of pixel intensities on the imprint along a drawn line and over a selected region, as well as plots that characterize pixel intensity and change in the thickness of the imprint along a drawn line; (2) expectations and variances for the intensities of the selected regions and intensity histograms; (3) extracted vessels and ischemia zones with their statistical descriptions; and (4) detected cells of hexagonal, pentagonal, and other shapes, as well as a set of characteristics associated with the size of the cells detected [19]. Figure 3 shows determining the characteristics of blood flow in the vessels of eye conjunctiva, such as linear and volumetric blood speed, and topological characteristics of vascular net.…”