Three stage red lesions detection using digital color retinal angiographies

Diabetic retinopathy prevention requires the screening of large numbers of patients, and examination of a huge amount of images, since diabetic patients typically have both their eyes examined at least once a year. To effectively manage all this information and the workload it produces, automatic techniques for analyzing the images are required. These techniques must be robust, sensitive and specific to be implemented in real-life screening applications. In this work an algorithm for the detection of red lesions in digital color fundus photographs is proposed. The method performs in three stages: in the first stage points candidates to be red lesions are obtained by using a set of correlation filters working in different resolutions, allowing that way the detection of a wider set of points. Then, in the second stage, a region growing segmentation process rejects the points from the prior stage whose size does not fit in the red lesion pattern. Finally, in the third stage three test are applied to the output of the second stage: a shape test to remove non-circular areas, an intensity test to remove that areas belonging to the fundus of the retina and finally a test to remove the points which fall inside the vessels (only lesions outside the vessels are considered). Evaluation was performed on a test composed on images representative of those normally found in a screening set. Moreover, comparison with manually-obtained results from clinical experts are performed, to set the accuracy and reliability of the method. Key–Words: Fundus, microaneurysm, red lesions, retina, screening, correlation.