Knowledge Hub

Abstract: Deep-learning-based Segmentation of Ellipsoid Zone And Geographic Atrophy On Real-World Optical Coherence Tomography

Method to use AI to automatically segment in optical coherence tomography (OCT) images of the retina where photoreceptor or retinal pigment epithelium cells are lost. This allows to quantify...

Abstract: Can AI provide more consistent fluid measurements in nAMD across OCT devices than humans?

Measurements of fluid in age-related macular degeneration differ between OCT devices, complicating clinical trials and care. We compared AI-based fluid measurements across two common devices...

Abstract: Automated Segmentations of Photoreceptor Degeneration and RPE Loss in Geographic Atrophy as factors to screen for fast progressors in real-world OCT data

RetInSight GA Monitor automatically segment loss of photoreceptor and retinal pigment epithelium (RPE) cells due to geographic atrophy (GA) secondary to age related macular degeneration. In...

Abstract: Using AI Uncertainty for Image Quality Assessment and Gradability of Retinal Thickness in OCT

A built-in uncertainty measurement from an AI layer model was used to detect poor image quality in OCT scans. Common artifacts were synthetically created (added noise, shadows from...

Interview: Artificial Intelligence (AI) in the management of retinal diseases

Artificial intelligence is becoming an important part of modern ophthalmology, and this YMO video podcast explores how it is already changing daily clinical practice in Europe.