An Efficient and Integrated Approach for the Detection of Blood Vessels and Exudates in Color Fundus Images

Diabetic-related eye disease is a major cause of preventable blindness in the world. It is a complication of diabetes which can also affect various parts of the body. When the small blood vessels have a high level of glucose in the retina, the vision will be blurred and can cause blindness eventually. This is known as diabetic retinopathy. Regular screening is essential in order detect the early stages of diabetic retinopathy for timely treatment to prevent or delay further deterioration. This paper detects the presences of abnormalities in the retina such as the structure of blood vessels, micro aneurysms, exudates and texture properties using image processing techniques. These features are input into artificial neural network for automatic detection and can quickly process a large number of fundus images obtained from mass screening to help reduce the cost and increase productivity and efficiency for ophthalmologists.