Retinal image classification using a histogram based approach

An approach to classifying retinal images using a histogram based representation is described. More specifically, a two stage Case Based Reasoning (CBR) approach is proposed, to be applied to histogram represented retina images to identify Age-related Macular Degeneration (AMD). To measure the similarity between histograms, a time series analysis technique, Dynamic Time Warping (DTW), is employed. The advocated approach utilises two “case bases” for the classification process. The first case base consists of green and saturation histograms with retinal blood vessels removed. The second case base comprises the same histograms, but with the Optic Disc (OD) removed as well. The reported experiments demonstrate that the proposed two stage classification process outperforms the single stage classification process with respect to a number of evaluation metrics: specificity, sensitivity and accuracy.

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