Pupil Edge Region Removal for Refractive Error Accuracy

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Solution Overview

Problem

Current medical digital imaging systems face challenges in accurately determining refractive errors, especially with smaller pupil sizes, due to the inclusion of glint and pupil edge region pixels in intensity distribution calculations, leading to inaccurate results.

Innovation Solution

The system identifies and removes glint and pupil edge region pixels by generating interpolated pupil data, determining a representative intensity, and applying a threshold to create a binary image, thereby improving the accuracy of refractive error calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If glint and pupil edge region pixels are included in intensity distribution calculations, then the calculation can be performed using all available pixels, but the measurement precision of refractive error deteriorates due to inaccurate intensity distribution

Engineering Contradiction:

Improvenumber of pixels used in calculationVSAvoidrefractive error determination accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent extracts and removes glint pixels and pupil edge region pixels from the intensity distribution calculation. By identifying these specific pixel types and excluding them from the analysis, the system maintains a sufficient number of valid pupil pixels while eliminating sources of measurement error, thereby improving refractive error determination accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies different quality criteria to different regions of the pupil image. Central pupil pixels are included in the calculation, while glint pixels (with specific intensity characteristics) and edge region pixels (with lower intensity values) are excluded. This local differentiation ensures that only pixels representing true pupil reflectance are used for refractive error calculation.

Inventive Principle:

Principle #3Local quality

2Ease of manufacture

If a simple threshold is used to remove pupil edge pixels, then the processing is simple, but the manufacturing precision of the mask deteriorates due to inability to handle glint areas

Engineering Contradiction:

Improveprocessing simplicityVSAvoidmask accuracy

Core Design Contradiction:

Ease of manufactureVSManufacturing precision

Solution Approach 1:

The patent segments the pupil pixel population into distinct categories: central pupil pixels, glint pixels, and edge region pixels. By dividing the pixel population into these segments based on their intensity characteristics and spatial location, the system can apply appropriate processing to each segment, resulting in an accurate mask that properly handles glint areas while maintaining processing simplicity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent performs preliminary identification and classification of pixel types before generating the final mask. By pre-categorizing pixels into glint, edge region, and central pupil groups based on intensity thresholds and spatial relationships, the system prepares the data structure needed for accurate mask generation, ensuring both simplicity and precision in the overall process.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10949969B1Pupil edge region removal in digital imaging

Publication Date: 2021.03.16 WELCH ALLYN INC

AI summary

A digital imaging system processes digital images of a subject's fundus and/or pupils to determine pupil edge region pixels. Pupil edge region pixels are removed and a glint area is identified and interpolated over. Resulting images can be processed to determine a pixel intensity distribution slope. Using the pixel intensity distribution slope, refractive error determinations can be made.