# Fully Convolutional Networks for Monocular Retinal Depth Estimation and Optic Disc-Cup Segmentation

## TL;DR

This paper introduces a fully convolutional neural network approach for monocular retinal depth estimation and optic disc-cup segmentation to improve glaucoma diagnosis from fundus images.

## Contribution

It proposes a novel deep learning framework that simultaneously estimates retinal depth and segments optic disc and cup from single fundus images.

## Key findings

- Achieved high accuracy in optic disc-cup segmentation.
- Demonstrated effective depth estimation from monocular images.
- Outperformed existing methods in glaucoma screening tasks.

## Abstract

Glaucoma is a serious ocular disorder for which the screening and diagnosis are carried out by the examination of the optic nerve head (ONH). The color fundus image (CFI) is the most common modality used for ocular screening. In CFI, the central r