Multiscale retinal vessel segmentation with precise width estimation

Abstract

Automated segmentation of blood vessels in retinal images can tell us about retinal, ophthalmic and even systemic diseases so that it can help ophthalmologists screen larger populations for vessel abnormalities. For example, the vessel width shows the abnormality of arterial narrowing, a serious damage caused by hypertension. Because the width of retinal vessels can vary from very large to very small, and the local contrast of vessels is unstable especially in unhealthy ocular fundus, the automated vessel segmentation with precise width estimation is a very difficult task. In this paper, we propose an efficient multiscale vessel segmentation scheme. Our scheme includes 1) Image resampling using Lanczos interpolation, 2) Scale production to enhance vessels, and 3) Multiscale morphological reconstruction to segment vessels in each scale. The experimental results demonstrate that the proposed scheme works well for accurately segmenting vessels with good width estimation.