A new way to extract blood vessels in digital images of the retina

Diabetic retinopathy is one of the most common causes of blindness in the world. Identifying blood vessels from retinal images plays an important role in diagnosing eye diseases such as diabetic retinopathy. Extraction of retinal blood vessels is done manually by a doctor, which is time-consuming and difficult and is associated with error due to individual dependence. Detecting small veins in retinal images is difficult due to low contrast and rotation. In this article, a new method for extracting blood vessels from digital retinal images is presented. This method consists of three basic parts. The first part deals with the removal of noise in retinal images. The second part deals with the extraction of the central lines of the vessel, and finally, using the method of expanding the area and removing the noise, blood vessels are extracted in the retinal images. The proposed algorithm is applied to the images of the DRIVE test set and the implementation results show that this algorithm has achieved an accuracy of 0.96578% in this data set.