Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images
We have developed automated Age-Related Macular Degeneration diagnosis system. Entropies, HOS, FD and Gabor wavelet features are extracted from fundus images. Various feature ranking methods are used to identify optimum features. The proposed system was evaluated using private, ARIA and STARE datasets. It yielded the highest average classification accuracies of 90.19%, 95.07% and 95%.
age-related macular degeneration entropy gabor wavelet texture higher order spectra computer aided diagnosis