A Semiautomatic Superpixel Based Approach to Cup-to-Disc Ratio Measurement

Glaucoma is a disease that affects the optic nerve, making it difficult to transmit impulses from the retina to the brain. This failure is caused by increased intraocular pressure and can lead to blindness. Early detection is the best alternative to mitigate the effects of glaucoma since the disease has no cure. This paper proposes a semi-automatic method to calculate the ratio between the diameters of the optic disc and cup. The approach begins repainting the blood vessels, minimizing their interference in the next steps. We perform the segmentation in two stages. Initially, we used the SLIC algorithm for superpixels generation. Subsequently, the algorithm Seeded Fuzzy C-means groups the superpixels based on a small percentage of data labeled by specialists. Then the images undergo a post-processing step eliminating noise and smoothing edges. This last phase aims to adapt the segmented images for the CDR calculation. We evaluated the method in 260 images from two public databases, DRISHTI-GS (101) and RIM-ONE r3 (159). The analysis reached an accuracy in the segmentation above 91% and a mean absolute error of 0.0779 in the CDR calculation.