Automation of the Detection of Pathological Changes in the Morphometric Characteristics of the Human Eye Fundus Based on the Data of Optical Coherence Tomography Angiography

This paper presents the results of the joint work of image analysis specialists and ophthalmologists on the task of analyzing images obtained by the method of optical coherence tomography angiography. A method was developed to automate the detection of pathological changes in the morphometric characteristics of the fundus. The solution of the image recognition problem assumes the presence of certain image representations, the presence of effective recognition algorithms, and the compliance of the used image representations with the requirements of the recognition algorithms for the source data. To reduce images to a form that is easy to recognize we considered sets of features that met all the necessary requirements of specialists. Chosen feature model was implemented to the problem of classification of images of patients with and without pathologies. The developed method makes it possible to classify pathological changes in the vascular bed of the human eye with high accuracy.