Abstract
The optic disc (OD) localization plays an important role in the automatic retinal image analysis for many applications such as glaucoma detection, macular localization, and retinal vessel analysis. In this paper, we propose a method based on U-net and Depth-First-Select Graph to accurately and efficiently locate the optic disc. The adopted U-net architecture is based on ResNet-50, and it predicts the center of OD and produces a probability map. Then based on the probability map, we use the Depth-First-Select algorithm to select the brightest and largest region, which is most likely to be the OD. The proposed method is evaluated on the ORIGA and Messidor dataset. Our experiment shows that the proposed method achieves 100% accuracy in ORIGA and 99.83% accuracy in Messidor. It outperforms other optic disc localization algorithms.
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