19/11/2025
New CERA research has shown an artificial intelligence system can accurately detect and measure distinctive deposits in the eye critical in the progression of age-related macular degeneration (AMD). 👁️
The findings open the possibility to study the not yet fully understood deposits at a scale previously thought impossible, accelerating research towards better treatments for the disease.
These deposits – called reticular pseudodrusen (RPD) – have previously been associated with a higher risk of progressing to late-stage AMD.
The deposits are not fully understood, and learning more about them requires looking at eye scans of many people who have them. However, identifying and measuring them is a challenge.
“Because of how they present on scans, identifying these deposits can be difficult for many clinicians,” says Associate Professor Zhichao Wu, the corresponding author of the study.
“And accurately quantifying or measuring their extent would be too prohibitively time-consuming to do manually.
“We want to be able to do large studies of hundreds or even thousands of people with these deposits to learn more about what they mean for age-related macular degeneration, but there aren’t the people or time to do it by hand.”
The AI model, developed alongside Dr Himeesh Kumar and University of Washington collaborators, has been publicly released so researchers around the world can use in their own work.
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