An automatic tracking method for retinal vascular tree extraction

In this paper, we propose an automatic tracking method to extract blood vessels in retinal images. Seed points are firstly picked out on a retinal image for initialization. Our algorithm detects vessel edge points iteratively based on a statistical sampling model using a Bayesian method. At a given step, local vessel´s sectional intensity profile is approximated by a Gaussian model. New vessel edge points are detected by using local grey level statistics and expected vessel structures. For evaluation purpose, we use the STARE public database. Experiments results show effective detection of blood vessels when using the proposed method.