Segmentation of exudates based on high pass filtering in retinal fundus images

Abstract

The World Diabetes Foundation has predicted that more than 439 million people in 2030 will suffer from diabetes. Long-term diabetics can lead to the damage of retinal blood vessels, known as diabetic retinopathy, the leading cause of blindness in developing countries. One of the clinical features of diabetic retinopathy is exudate. Exudates have similar characteristic with optic disc. Therefore, in this research work, removal of optic disc is conducted to reduce false positive of exudates detection. The optic disc detection is done by finding the small area of the optic disc which is enlarged to obtain its total area. Green channel that contains useful information for exudates detection is filtered based on high pass filter. Afterwards, segmentation of exudates is conducted by using thresholding and morphological operations. Final result of exudates is validated with ground truth images by measuring accuracy, sensitivity and specificity. The results show that proposed approach for exudates detection achieves accuracy, sensitivity and specificity of 99.99%, 90.15% and 99.99%, respectively. This result indicates that the proposed method successfully detects exudates and is useful to assist the ophthalmologists in analysing retinal fundus image especially for exudates detection to diagnose diabetic retinopathy.