Sub-Pixel Retinal Vessel Tracking and Measurement Using Modified Canny Edge Detection Method

Abstract

This article presents a new method to track and measure retinal blood vessel with sub-pixel accuracy. The method is based on a modified Canny edge detection method and a Gaussian model of the vessel profile and zero cross of second order derivative of the Gaussian model. In this method, Canny edge detection method is used at first to detect edges from an input retinal image. The edge orientation is then refined and used to obtain vessel cross-sectional profile. Vessel sample profile is searched using local maximum and local minimum from the smoothed vessel cross-sectional profile. Gaussian model is then used to fit the vessel sample profile. The zeros cross of the second order derivatives of the Gaussian fit vessel sample profile are then used to represent the boundaries of the blood vessels. The peaks of the Gaussian fits are then used as positions of vessel center lines and to calculate the widths of the vessel at those points. The method outputs vessel wall positions, the center lines of the vessels with the widths of the vessels with respect to center points in sub-pixel accuracy.