This paper introduces a systematic approach for segmentation of retinal blood vessels towards the diagnosis of proliferative diabetic retinopathy (PDR) from digital fundus images. Here, 2D-Match (Gabor) filters are used on digital fundus images in which the vessels are enhanced by contrast-limited adaptive histogram equalization (CLAHE). A double sided thresholding scheme is then used to segment the vessels. Hysteresis thresholding is performed with the large and small vessels clipped at different intensity levels in order to reconstruct the vessels in the image. This vessel extraction technique leads to high accuracy (93.1%) in comparison with the ground truth images provided in the DRIVE database.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Artificial Intelligence