Ocular Image Conversion Factor Lookup Table
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Solution Overview
Problem
Existing coordinate remapping approaches for calculating ocular feature size in ocular imaging systems are resource-intensive, particularly in applications involving high-frame-rate narrow-field images, making them inefficient for real-time processing.
Innovation Solution
An apparatus and method that evaluate a conversion factor for calculating distances between ocular features by obtaining scan parameters from ocular imaging data, using a mapping between scan parameters and conversion factors to convert pixel distances to physical distances, and storing the digital image with the determined conversion factor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If coordinate remapping approach is used to calculate ocular feature size, then measurement precision is improved, but device complexity and computing resource requirements increase
Solution Approach 1:
The patent pre-calculates conversion factors at different scan locations and stores them in a lookup table before actual imaging. When processing images, the system simply retrieves the appropriate conversion factor based on scan parameters rather than performing complex coordinate remapping calculations in real-time. This preliminary preparation reduces computational complexity during operation while maintaining measurement precision.
Solution Approach 2:
The patent creates a simplified model by copying only the essential relationship between scan parameters and conversion factors into a lookup table. Instead of implementing the full coordinate remapping mathematical model during processing, the system uses pre-computed values that replicate the essential functionality, reducing computational requirements while preserving measurement accuracy.
2Productivity
If coordinate remapping and distance calculation operations are performed at high frame rates, then productivity is improved, but computing resource consumption increases
Solution Approach 1:
Conversion factors are pre-calculated and stored in a lookup table based on scan parameters before high-speed imaging begins. During high-frame-rate processing, the system only needs to retrieve pre-computed values rather than performing complex calculations for each frame, enabling high productivity with reduced computational resource consumption.
Solution Approach 2:
The patent changes the computational approach from performing complex coordinate remapping calculations for each pixel in each frame to using pre-computed conversion factors that depend only on scan parameters. This parameter-based approach allows high-frame-rate processing because the conversion factors can be retrieved and applied without intensive computation for each image frame.
Data Source
AI summary
A technique for generating a mapping relating values of a scan parameter of an ocular imaging apparatus that are indicative of scan locations in an eye at which the apparatus acquires digital images of imaged regions of the eye, to respective values of a conversion factor for calculating a distance between designated ocular features in the imaged regions, by: simulating light ray propagation to relate each value of the scan parameter in a sequence of scan parameter values to a corresponding location in a model eye; calculating, for each scan parameter value, a distance between the corresponding location in the model eye and a location in the model eye corresponding to an adjacent value in the sequence; and using the calculated distances to generate a respective value of the conversion factor for each scan parameter value.