General Retinal Vessel Segmentation Using Regularization-Based Multiconcavity Modeling

—Detecting blood vessels in retinal images with the presence of bright and dark lesions is a challenging unsolved problem. In this paper, a novel multiconcavity modeling approach is proposed to handle both healthy and unhealthy retinas simultaneously. The differentiable concavity measure is proposed to handle bright lesions in a perceptive space. The line-shape concavity measure is proposed to remove dark lesions which have an intensity structure different from the line-shaped vessels in a retina. The locally normalized concavity measure is designed to deal with unevenly distributed noise due to the spherical intensity variation in a retinal image. These concavity measures are combined together according to their statistical distributions to detect vessels in general retinal images. Very encouraging experimental results demonstrate that the proposed method consistently yields the best performance over existing state-of-the-art methods on the abnormal retinas and its accuracy outperfo...

• Type: Journal
• Year: 2010
• Where: TMI
• Authors: Benson S. Y. Lam, Yongsheng Gao, Alan Wee-Chung Liew
• Keywords: Concavity Measures, Retinal Images, Retinas, TMI 2010