A multiscale approach to retinal vessel segmentation using gabor filters and scale multiplication

This paper presents a new approach to automated retinal vessel segmentation based on multiscale analysis and adaptive thresholding. The accurate identification of the appearance of blood vessels in ocular fundus plays an important role in medical diagnosis of many diseases. In contrast to the existing methods for computer aided diagnosis which are either window-based or tracking based, we propose a novel scheme which combines multiscale analysis and adaptive thresholding to help eye care specialists to screen larger populations for vessel abnormalities under various conditions such as vessel size and local 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.