Optic Disk and Cup Segmentation Through Fuzzy Broad Learning System for Glaucoma Screening

Glaucoma is an ocular disease that causes permanent blindness if not cured at early stage. Cup-to-disk ratio (CDR), obtained by dividing the height of optic cup (OC) with disk (OD), a widely adopted metric used for glaucoma screening. Therefore, accurately segmenting OD and OC crucial calculating CDR. Most methods have employed deep learning segmentation OC. However, these are very time consuming. In this article, we present new fuzzy broad system-based technique We comprehensively integrated extracting region interest from RGB images, data augmentation, red green channel inputting them to two separate neural networks OC, respectively, then calculated Experiments show our outperforms many state-of-the-art methods.