A Novel and Efficient Hybrid Segmentation Approach for Retinal Vasculature Network

Segmentation of retinal vasculature network is vital for the timely identification of various eye diseases. In this work, an automated hybrid segmentation technique for retinal vasculature network is proposed. Unlike the other techniques, the proposed method uses separate segmentation techniques for thick and thin retinal vessels. As a result, both vessels are retained in the final segmented result thereby improving the final segmentation accuracy. Enhancement technique used for retinal images can significantly affect the final segmentation result. Rather than using conventional enhancement techniques, for the improved enhancement, Frangi vesselness filter is used. The proposed technique is evaluated on STARE, DRIVE, and a database developed by the authors from the images collected from Shanghai Sixth Peoples Hospital.