Scientiic Visualization Techniques for Displaying Corneal Shape

The shape of the cornea has a large eeect on visual performance. Recent advances in corneal topography measurement technology can provide detailed information about the subtle shape of the corneal surface. This data is desired by a variety of professionals, including clinicians, surgeons , and vision scientists. However, for this complex data to be useful, it must be presented in a way that can be interpreted accurately and eeciently. Such a problem is well-suited for a computer graphics solution using scientiic visualization methods. We propose several visualization techniques and describe a suite of visualization software implementing these techniques. 1 Motivation Knowledge of the corneal contour is becoming increasingly important for clinical purposes, including the tting of contact lenses, planning and evaluating corneal surgery, and diagnosing keratoconus. Equally important is the communication of this data to clinicians in a meaningful form. A number of methods for communicating this data already exist, but have some shortcomings. We propose several corneal visualization techniques and present a corresponding suite of visualization software. 2 Corneal Topography Measurement Corneal surface data is useful in many areas of eye care, and sophisticated methods and instruments have been developed to measure this data. 2.1 Videokeratography The videokeratograph is an instrument with a conically-shaped target containing luminous rings. 4] A video camera is mounted at the center of the target to record the reeected image. The video camera takes a digital picture of the reeected ring pattern which can then be analyzed by a computer. The corneal shape can be recovered from this image with a high degree of accuracy. 3] 2.2 Data Reconstruction As mentioned above, corneal shape data retrieved from a videokeratograph can be analyzed by a computer. The visualization software described in this paper uses such data. However, the data output from a videokeratograph is in the form of sample values rather than a full surface description. A smooth mathematical surface must be reconstructed before the shape data can be used by visualization software. An algorithm for reconstructing a smooth surface is described in a related paper. 2]