Estimating the shape of the human eye using widefield optical coherence tomography (OCT)

Widefield optical coherence tomography (OCT) can be used to image the posterior segment of the human eye. OCT images are typically distorted due to the inconsistent scanning and display geometry and the refractive properties of the human eye. The goal of this study was to create and validate an estimation model that maps the OCT images to the true geometry of the human eye. In addition, we wanted to assess how refractive parameters of the human eye and instrument-to-eye alignment errors affect the estimation model. We have developed a model that estimates the true curvature of the posterior human eye based on widefield OCT images. We have experimentally validated the estimation model using two different phantoms, a single refractive surface solid glass test eye with a spherical retina, and a waterfilled test eye with anatomically correct cornea, lens, iris, and retina. In order to further evaluate the suitability of the model to estimate the shape of the human eye, we have performed a tolerance analysis of the critical alignment and refractive parameters in the model, including axial length, corneal power, refractive indices, and lateral and axial alignment of the eye relative to the OCT system. We have found the estimation model to be highly sensitive to variations in axial length and less sensitive to variations in working distance, corneal power, eye alignment, or refractive indices. In conclusion, we have demonstrated an estimation model that estimates the shape of the human eye based on widefield OCT imaging. We further conclude that we can appropriately estimate the shape of the human eye based on widefield OCT images by using nominal values for the refractive properties and actual measurements of the axial length of the eye.