MFCA: Matched Filters with Cellular Automata for Retinal Vessel Detection

Blood vessel extraction is an important step for abnormality detection and for obtaining good retinopathy diabetic diagnosis in digital retinal images. The use of filter bank has shown to be a powerful technique for detecting blood vessels. In particular, the Matched Filter is appropriate and efficient for this task and in combination with other methods the blood vessel detection can be improved. We propose a combination of the Matched Filter with a segmentation strategy by using a Cellular Automata. The strategy presented here is very efficient and experimentally yields competitive results compared with others methods of the state of the art.