System and method of corneal surface measurement augmented for machine ingestion

Abstract

Methods, systems, and apparatus for illumination of the cornea of an eye are disclosed; in some implementations, such methods, systems, and apparatus may generally comprise or employ a light source and an optical mask, alignment of a viewing portal, and capture of a cornea-reflected image using a camera or other optical array. In some implementations, a system and method may generally comprise or involve generating data that are optimized for ingestion by an artificial intelligence or machine learning engine, thereby facilitating contact lens selection or detection of keratoconus or “dry eye” conditions for ophthalmic, optometric, and pediatric practices. Specifically, the disclosed subject matter teaches innovative cornea-reflective patterns, the reflections of which are designed for ingestion by statistical, machine learning, or artificial intelligence models.

Dependencies are inferred from the claim text.