A new and efficient vessel segmentation method from color retinal images
Retinal blood vessel changes (e.g., vessel caliber) are important indicators for earlier diagnosis of cardiovascular diseases. To quantify the changes automatically, a reliable vessel detection is essential. However, blood vessel detection in retinal image is complicated by a huge variation in a number of factors such as local contrast, vessel width and vessel central reflex. In this paper, we propose a new technique to detect retinal blood vessels which is able to address these issues. The core of the technique is a new vessel edge selection method which combines the method of finding edge pattern and edge profiling techniques. Experimental results show that 92.40% success rate in the identification of vessel start-points and 88.73% success rate in tracking the major vessels.
