Figure 1.

Deep learning system for automated segmentation in fundus images. The algorithm included two stages: optic disc (OD) region detection and OD and optic cup (OC) segmentation. For a given fundus image (a), the U-Net network (b) was utilized to detect the OD region (c). With the cropped OD region (d), a polar transformation was used to map the image into polar coordinate (e). A multilabel network (f) segmented the OD and OC jointly, and an inverse transformation returned the output map (g) back to original coordinates (h).