Exudate Detection in Fundus Images: Multispace Clustering Approach

Retina is the outer lining of human eye where the image formation takes place. Any threat to retina causes severe eye defects and may lead to complete blindness. During a defect the retina gets distorted. To measure the severity of a disease we need to determine different damage causing elements. Exudates are one such artefact that play a vital role in disease prediction. Diabetic Retinopathy is the leading cause of blindness in the working-age population of the world. Exudates act as a feature to predict this condition. This work aims to automatically segment exudates from fundus images using Image Processing and Machine Learning algorithms.