Posterior Corneal Surface Mapping Using Multi-Camera Ray Tracing
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Solution Overview
Problem
Existing devices for measuring the posterior corneal surface of an eye, such as OCT, Scheimpflug, and Purkinje systems, are either expensive with moving components or suffer from weak signals, making them unfavorable in certain situations.
Innovation Solution
A system utilizing multiple cameras and ray-tracing technology to determine the shape of the posterior corneal surface by tracing rays through the anterior and posterior surfaces of the cornea, optimizing parameters to align and minimize distances between camera images, and calculating the posterior surface shape based on Snell's Law and known refractive indices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If OCT or Scheimpflug devices are used to measure the posterior corneal surface, then measurement capability is achieved, but device cost and complexity increase due to moving components
Solution Approach 1:
The patent replaces mechanical moving components (OCT scanners, Scheimpflug rotating cameras) with a static multi-camera photogrammetric system. Multiple fixed cameras capture images simultaneously, and ray-tracing algorithms computationally determine the posterior corneal surface without any moving parts, thereby reducing device complexity while maintaining measurement capability
Solution Approach 2:
The system creates multiple optical copies (images) of the eye from different camera angles. By capturing images from multiple static cameras positioned at different locations, the system obtains sufficient information to reconstruct the posterior corneal surface through computational ray-tracing, eliminating the need for mechanical scanning
2Measurement precision
If Purkinje devices are used to measure the posterior corneal surface, then measurement is possible, but signal strength is weak
Solution Approach 1:
The patent merges data from multiple camera images taken at different angles and positions. By combining the optical information from multiple static cameras, the system accumulates sufficient signal strength to accurately determine the posterior corneal surface through ray-tracing, overcoming the weak signal limitation of single-camera Purkinje devices
Solution Approach 2:
The system transitions from single-point or single-line measurement to three-dimensional surface mapping by incorporating spatial information from multiple cameras positioned at different locations. This multi-dimensional approach provides redundant optical paths that strengthen the overall signal for posterior surface determination
3Measurement precision
If multiple cameras and ray-tracing algorithms are used, then measurement precision is improved, but computational complexity increases
Solution Approach 1:
The patent performs preliminary measurements of the anterior corneal surface using standard corneal topography before applying ray-tracing algorithms. This pre-acquired anterior surface data serves as known input constraints that simplify the computational inversion process, reducing the complexity of determining the posterior surface while maintaining high precision
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately measures the posterior corneal surface with improved precision and cost-effectiveness by leveraging off-axis and on-axis cameras and ray-tracing algorithms, providing detailed surface maps.
Implementation Method 1
tracing rays through the anterior and posterior surfaces of the cornea, optimizing parameters to align and minimize distances between camera images, and calculating the posterior surface shape based on Snell's Law and known refractive indices
Data Source
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AI summary
In certain embodiments, a system for measuring the posterior corneal surface of the cornea comprises cameras and a computer. Each camera generates image data representing a part of the eye posterior to the cornea. The image data describes locations of features of the part. The computer stores a description of the shape of an anterior corneal surface of the cornea, and applies a ray-tracing process to determine the shape of the posterior corneal surface. The ray-tracing process comprises defining rays, where each ray is traced from a camera, through the anterior and posterior corneal surfaces, and to the part of the eye. Constraints for the rays are determined, where the constraints are calculated using the description of the shape of the anterior corneal surface and locations of the features in the image data. Parameters are optimized, and the optimized parameters describe the shape of the posterior corneal surface.