Computer Algorithm for Simulation of the Human Optical System and Contribution of the Cornea to the Optical Imperfections of the Eye

The main objective of this work is to demonstrate the relation between corneal surface imperfections and retinal image imperfections. Its originality resides on the fact that specialized literature approximate the eye and the cornea as mathematical surfaces to explain simple refraction problems (myopic, hyperopic, astigmatic), whereas in the present work we have used topographic data for in vivo corneas and other refractive imperfections may be analyzed. This data was collected in a specialized instrument denominated Corneal Topographer. With this true corneal data we could understand how more complex imperfections, directly related to more delicate surface curvature differences, degrade the retinal images. It is well known that the cornea contributes to approximately 2/3 of the total refraction of the eye. Nevertheless, there is very few knowledge of its contribution to the optical aberrations of the images formed at the retina. Most corneal diagnostic equipments (Corneal Topographers and Keratometers) measure only its dioptric power (proportional to curvature) and, in certain cases, shape, but do not calculate or estimate the corneal contribution to the quality of image formation at the retina. On the other hand, auto-refractors and wave-front sensors measure the optical aberrations of the eye as a single optical “device”, and therefore do not indicate individual contributions. We have developed algorithms that read elevation data from a commercial corneal topographer and use this data and ray-tracing algorithms to estimate the image quality formed at the retina. Conventional optical design test functions such as the Point Spread Function (PSF) and longitudinal shift in focus position, together with the two-dimensional curvature maps obtained from corneal topography, are plotted and used to analyze retinal image quality.