The paper presents the results of research and development of a modern information and measurement
system (IMS) designed for automated analysis of fundus images for the purpose of diagnosing and
monitoring ophthalmic pathologies. The proposed system combines methods of digital medical image
processing, artificial intelligence and computer vision, which allows ensuring high accuracy and
objectivity of the diagnostic process. Particular attention is paid to the use of deep learning algorithms for
the segmentation of anatomical structures of the retina and analysis of fluorescent images. A
comprehensive method of photodynamic diagnostics and therapy has been developed, which is
implemented based on a modified slit lamp with a laser illuminator. Effective methods of image
registration and processing have been proposed, in particular their synchronization and spectral analysis,
which allows for quantitative assessment of the state of tissues. The results of the study can be used in
ophthalmological practice to increase the accuracy of early detection of pathologies, as well as in
telemedicine and personalized medicine systems.
