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In this study, a supervised retina blood vessel segmentation process wasperformed on the green channel of the RGB image using artificial neural network(ANN). The green channel is preferred because the retinal vessel structures canbe distinguished most clearly from the green channel of the RGB image. Thestudy was performed using 20 images in the DRIVE data set which is one of themost common retina data sets known. The images went through some preprocessingstages like contrastlimited adaptive histogram equalization (CLAHE), colorintensity adjustment, morphological operations and median and Gaussianfiltering to obtain a good segmentation. Retinal vessel structures werehighlighted with top-hat and bot-hat morphological operations and converted tobinary image by using global thresholding. Then, the network was trained by thebinary version of the images specified as training images in the dataset andthe targets are the images segmented manually by a specialist. The averagesegmentation accuracy for 20 images was found as 0.9492.

Supervised Segmentation of Retinal Vessel Structures Using ANN