project
Fundus Imaging Research
Collaborative research on automated screening for diabetic retinopathy using deep learning on retinal fundus images.
This research focused on the application of convolutional neural networks to identify early signs of retinopathy in high-resolution fundus photography.
The primary objective was to increase the throughput of screening in high-volume environments like Aravind Eye Hospital. By automating the preliminary tier of triage, we aimed to allow specialists to focus on the most severe cases, effectively scaling the impact of specialized eye care.