Retinal vessel segmentation using local relative entropy thresholding

Performing the segmentation of vasculature in the retinal images having pathology is a challenging problem. This paper presents a novel approach for automated segmentation of the vasculature in retinal images. The approach uses the intensity information from red and green channels of the same retinal image to correct non-uniform illumination in colour fundus images. Matched filtering is utilized to enhance the contrast of blood vessels against the background. The enhanced blood vessels are then segmented by employing local relative entropy based thresholding which can well maintain the spatial structure of the vascular tree segments. Experimental evaluation of the proposed algorithm demonstrates superior performance over other vessel detection algorithms recently reported in the literature.