Novel Algorithm to Differentiate Astigmatism from Keratoconus

Abstract

Astigmatism is a very common eye disorder. The cornea of the normal eye has a uniform curvature, with resulting equal refracting power over its entire surface. Light rays refracted by this cornea are not brought to a single point focus, and retinal images from objects both distant and near are blurred and may appear broadened or elongated. This refractive error is called astigmatism. Keratoconus is an ecstatic dystrophy characterized by progressive thinning, steepening, and apical conic protrusion of the cornea. Keratoconus can cause substantial distortion of vision, with multiple images, streaking and sensitivity to light. Symptoms are similar in both of the two diseases that make it difficult even for experienced ophthalmologists to make a decision on some cases whether they are keratoconic or only astigmatic eyes. Diagnosis of these visual disorders has been developed vastly in the last two decades. The existing methods are either diagnosing astigmatism or keratoconus separately or classify those using different techniques. The proposed algorithm is novel and simple method for diagnosing astigmatism and keratoconus and classifying them by combining the latest topographic facilities along with image processing techniques. One of the most popular topographic and pachemetry machines is PENTACAM, due to its high precision and quality of Pentacam images (colour coded maps), the unharmed technology, ease of use and availability. Physicians interpret the colour coded images to diagnose & treat patients with eye refracting issues manually. In the proposed work, an attempt has been made to make this process computerized by means of image processing techniques.