Fluorescein angiography (FA) and autofluorescence (AF) imaging are two forms of gray scale retinal images that are currently taken at ophthalmology practices and interpreted by retinal specialists. They are useful in monitoring extent and progression of retinal diseases, such as age-related macular degeneration (AMD) and diabetic eye disease. 

One main challenge in using this current imagining technology is that the interpretation is subjective. It suffers from inter-physician variability and lacks a quantitative measure for disease burden. Our project is developing Machine Learning and Computer Vision approaches to the automated analysis of retinal FA and AF imaging.

Associated Publications:
 

• Automated Detection of Fluorescein Leakage in Diabetic Macular Edema - Association for Research in Vision and Ophthalmology, 2013