Vessel cross-sectional diameter measurement on color retinal image

Abstract

Vessel cross-sectional diameter is an important feature for analyzing retinal vascular changes. In automated retinal image analysis, the measurement of vascular width is a complex process as most of the vessels are few pixels wide or suffering from lack of contrast. In this paper, we propose a new method to measure the retinal blood vessel diameter which can be used to detect arteriolar narrowing, arteriovenous (AV) nicking, branching coefficients, etc. to diagnose various diseases. The proposed method utilizes the vessel centerline and edge information to measure the width for a vessel cross-section. Using the Adaptive Region Growing (ARG) segmentation technique we obtain the edges of the blood vessels, and then applying the unsupervised texture classification method we segment the blood vessels from where the vessel centerline is obtained. The potential pixels pairs for each centerline pixel are obtained from the edge image that pass through this centerline pixel. We apply a rotational invariant mask to search the pixel pairs from the edge image, and calculate the shortest distance pair which provides the vessel width (or diameter) for that cross-section. The method is evaluated with manually measured width for different vessels' cross-sectional area. For the automated measurement of vascular width we achieve an average accuracy of 95.8%. © 2008 Springer-Verlag.