Optic Nerve Head

The optic nerve head (ONH), the point where the optic nerve exits the eye, is a critical area of study for diagnosing and managing glaucoma and other ophthalmic diseases. Current research heavily utilizes 3D optical coherence tomography (OCT) imaging coupled with advanced deep learning techniques, including convolutional neural networks (CNNs), transformers, and geometric deep learning methods like PointNet and graph convolutional networks, to analyze ONH structure and improve diagnostic accuracy. These AI-driven approaches aim to identify key 3D structural features within the ONH, such as lamina cribrosa deformation and retinal nerve fiber layer thickness, to better differentiate between healthy and diseased states, ultimately improving glaucoma detection and management. This work holds significant promise for improving the speed and accuracy of diagnosis, potentially leading to earlier interventions and better patient outcomes.