Independent Component Analysis for Vision-inspired Classification of Retinal Images with Age-related Macular Degeneration

The purpose of this paper is to present a novel approach for extracting image-based features for classifying age-related macular degeneration (AMD) in digital retinal images. 100 retinal images were classified by an ophthalmologist into 12 categories based on the visual characteristics of the disease. Independent Component Analysis (ICA) was used to extract features at different spatial scales to be used as input to a classifier. The classification used a type of regression, partial least squares. In this experiment ICA   replicated the ophthalmologist's visual classification by correctly assigning all 12 images from two of the classes.