A new approach to automated retinal vessel segmentation using multiscale analysis

Computer based analysis for automated segmentation of blood vessels in retinal images will help eye care specialists screen larger populations for vessel abnormalities. However, automated retinal segmentation is complicated by the fact that the width of retinal vessels can vary from very large to very small, and that the local contrast of vessels is unstable, especially in unhealthy ocular fundus. We propose a novel method that takes these facts into account. Our method includes a multiscale analytical scheme using Gabor filters and scale production, and a threshold probing technique utilizing the features of retinal vessel network. Our method is good for detecting large and small vessels concurrently. It also offers an efficient way to denoise and enhance the responses of line filters, allowing the detection of vessels with low local contrast.