Detection and decision-support diagnosis of diabetic retinopathy using machine vision

This invited paper considers the results of the IMAGERET project. The goal of the project is to demonstrate how lesions in a retina caused by diabetic retinopathy can be detected from color fundus images by using machine vision methods. The project consists of the following results: an image annotation tool for medical expert annotation, diabetic retinopathy databases, an evaluation framework for development and comparison of methods, image-based and pixel-based methods, and new imaging solutions. The automated diagnosis can be seen in two steps: in the first step, it is decided whether an eye needs further analysis (too many lesions visible) or not (the eye is healthy enough). In the second step, fundus images selected for further analysis are automatically diagnosed. The developed system saves both resources of medical experts and costs in healthcare. It will further offer a tool for the health care providers to improve the quality of the life of diabetes patients. This is important since the number of diabetes patients is increasing, especially rapidly in the developed countries.