AUTOMATED IDENTIFICATION OF EYE DISEASES USING HIGHER-ORDER SPECTRA

A computer-based intelligent system for the classification of eye diseases can be very useful for their diagnosis and management. With age, the incidence of ocular pathology rises, thereby decreasing normal eye function. The most common causes of age-related eye disorders and visual impairment in the elderly are cataracts and iridocyclitis (inflammation of the iris, i.e. the colored part of the eye, and of the ciliary body). For proper care and management of eyes, we need a system which can automatically classify these eye diseases. The method proposed in this study is based on higher-order spectral (HOS) features that capture contour and shape information, while providing robustness to shift, rotation, changes in size, and noise. The parameters are extracted from the raw images using the HOS techniques, and fed to the classifiers for classification. This paper presents the classification of three kinds of eye classes using four-layer feedforward and Gaussian mixture model (GMM) classifiers. Our protocol used 122 subjects who had three different kinds of eye disease conditions. We demonstrated a sensitivity of 100% for the classifier, with a specificity of 90%. Our systems are clinically ready to test on large data sets.