Automatic detection of laser marks in retinal digital fundus images

Diabetic retinopathy (DR) is the most frequent complication of diabetes mellitus that affects vision to the point of causing blindness. In advanced stages its progress can be delayed with laser photocoagulation which leaves behind marks on the retina. Modern screening programs rely on automatic diagnostic algorithms to detect signs of DR in patients. These systems performance may be impaired when patient retina presents marks from previous laser photocoagulation treatments. Since these patients are already being treated, it is desirable to detect and remove them from the screening program. An algorithm that automatically detects the presence of laser marks in retinal images using tree-based classifiers is proposed and the results on its performance are obtained and described. Two new public accessible datasets containing retinal images with laser marks are provided in this paper.

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