Ophthalmic Lens Surface Modeling for Faster Personalized Calculation
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Solution Overview
Problem
Conventional methods for calculating ophthalmic lenses face challenges with increasing computation time and storage requirements as the number of order parameters increases, leading to inefficiencies and quality losses, especially in individualized or personalized lenses.
Innovation Solution
A computer-implemented method using a surface model to directly calculate ophthalmic lens surfaces from a set of order parameters with optimized model parameters, reducing computation cost and storage requirements by employing machine learning algorithms and regression models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional calculation methods are used for ophthalmic lenses, then the calculation can be performed with simple algorithms, but the computation time increases significantly and storage requirements increase as the number of order parameters increases
Solution Approach 1:
The patent uses pre-calculated lookup tables that store surface parameters for different order parameter combinations. Instead of performing complex calculations in real-time, the system retrieves pre-computed values from these tables, effectively copying previously computed results to avoid redundant computation. This dramatically reduces computation time while maintaining accuracy for standard lens designs.
Solution Approach 2:
The patent performs complex calculations in advance during a preprocessing stage, storing the results in lookup tables. When actual lens calculation is needed, the system simply retrieves pre-computed values rather than performing the full calculation anew. This preliminary action eliminates the need for time-consuming real-time optimization computations.
2Adaptability or versatility
If optimization methods are used for individualized spectacle lenses, then the lens can be tailored to specific wearer requirements, but the computation time for each optimization pass becomes increasingly longer
Solution Approach 1:
For individualized lenses, the system uses lookup tables that store pre-optimized surface parameters for various wearer-specific scenarios. When a new individualization request comes in, the system retrieves the appropriate pre-computed surface parameters based on the wearer's characteristics, avoiding the need to perform time-consuming optimization calculations for each individual case.
Solution Approach 2:
The patent transforms the optimization problem into a parameter lookup problem by pre-calculating surfaces for a range of possible order parameter values and storing them in lookup tables. This allows the system to handle individualized requirements by simply changing which pre-computed parameters are retrieved, rather than performing new optimizations for each unique wearer profile.
3Device complexity
If direct calculation methods are used for simple surfaces, then the computation cost is low, but the method cannot handle complex individualized lenses with multiple parameters
Solution Approach 1:
The patent segments the calculation process into two distinct parts: a preprocessing phase where complex surfaces are calculated and stored in lookup tables, and a runtime phase where simple parameter retrieval occurs. This segmentation allows the system to handle complex individualized lenses during preprocessing while maintaining low computation costs during actual lens calculation through simple table lookups.
Data Source
AI summary
Method for determining a surface model for calculating a surface of an ophthalmic lens from a set of order parameters for the lens or from variables depending on the order parameters. The method includes providing a training data set having order parameter sets; providing a target value of a property of the lens for each of the order parameter sets; providing a surface model with parameters; and determining optimized values for the parameters using the provided target values by optimizing the values for the parameters by minimizing/maximizing a target function for the parameters. The target function for the parameters for each of the order parameter sets has a term which assumes a minimum/maximum when the provided target value coincides with the value of the same property of a lens which is calculatable with the surface model for given values of the parameters for the corresponding order parameter set.