Using fast marching in automatic segmentation of retinal blood vessels

Abstract

The appearance of blood vessels in retinal images plays an important role in diagnosis of many eye diseases and system diseases. This presentation investigates a novel algorithm for automatic segmentation of blood vessels in retinal images by using vessel enhancement techniques and Fast Marching (FM) method. The algorithm includes the following major steps: Morlet wavelet transform, curvature estimation, matched filtering, and Fast Marching. The wavelet transform and the curvature-based method are first applied to detect the skeleton of vessels, which serve as the initial seeds of the Fast Marching algorithm. The matched filter is then used to enhance the vessels in order to extract the features used by the Fast Marching's velocity function. Finally, the Fast Marching algorithm is applied to obtain final segmentation of retinal blood vessels. This algorithm provides effective segmentation results of retinal vessels, which can be analyzed in later processing stages leading to a complete diagnosis system. © 2008 Springer-Verlag.