Automated retinal vessel segmentation using Gabor filters and scale multiplication

The accurate identification of the appearance of blood vessels in ocular fundus plays an important role in medical diagnosis of many diseases. The automated segmentation is helpful for eye care specialists to screen larger populations In contrast to the existing methods for computer aided diagnosis which, we propose a novel scheme which combines multiscale analysis and adaptive thresholding for vessel segmentation under various abnormal conditions such as vessel size and low contrast. Our method includes a multiscale analytical scheme based on Gabor filters and scale multiplication, and adaptive thresholding. The experimental results demonstrate the feasibility and effectiveness of the proposed algorithms which are good for detecting large and small vessels concurrently with robustness to denoise and enhance the responses at low contrast.