Automated System for the Personalization of Retinal Laser Treatment in Diabetic Retinopathy Based on the Intelligent Analysis of OCT Data and Fundus Images

Abstract

AbstractIn this work, we propose an automated system for the personalization of retina laser treatment in diabetic retinopathy. The system comprises fundus images processing methods, algorithms for photocoagulation pattern mapping, and intelligent analysis methods of OCT data and fundus images. The feasibility of introducing corrections at any interim stage of data processing makes for a safe treatment. A key module of the proposed software architecture is the system for the intelligent analysis of the photocoagulation pattern, allowing the proposed plan to be analyzed and the treatment outcome to be prognosticated. Working with the proposed system, the surgeon is able to map an effective photocoagulation pattern, which is aimed at providing a higher-quality diabetic retinopathy laser treatment when compared with the current approaches. The software developed is intended for the use of high-performance algorithms that can be parallelized using either a processor or a graphics processing unit. This allows achieving high data processing speed, which is so important for medical systems.KeywordsFundusLaser CoagulationDiabetic RetinopathyImage Processing; Segmentation; Classification