Abnormalities detection in retinal fundus images

The development of an automatic telemedicine system for screening and grading of Diabetic Retinopathy depends (DR) on reliable detection of abnormalities in retinal fundus images. The abnormalities in retinal fundus images due to DR are lesions which includes Micro aneurysms and Haemorrhages. An automatic detection of abnormalities like Micro aneurysm and Haemorrhages in colour fundus images is important to grade the diabetes level of patients in an automated system. The proposed method to detect the abnormalities in retinal fundus image is based on dynamic shape features and SVM classifier. Red lesion detected using two important aids. The first is candidate detection based on pixel classification. Using this technique vasculature and red lesions are separated from the back ground of the image. After removal of the connected vasculature the remaining objects are considered possible red lesions. Second the detected candidates are used to train the Support Vector Machine (SVM) classifier. The abnormalities detection accuracy of the proposed method is about 90% for diartedb1 database and 80% for stare database by cross training.