Spectral Sensor Calibration for Artifact Removal in Eye Imaging
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Solution Overview
Problem
Ophthalmic devices introduce artifacts into spectral images of the eye, complicating diagnostic analysis due to varying optical configurations, illumination powers, and environmental conditions, making calibration difficult and costly, and limiting their use in diagnosing neurodegenerative diseases.
Innovation Solution
A method and system for calibrating spectral sensors by identifying and removing artifacts using reference data packages captured under specific operating characteristics, including optical configurations and illumination powers, to generate accurate multi-dimensional spectral data packages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If complex optical equipment with adjustable lenses is used to capture spectral images, then the ability to examine the eye is improved, but artifacts are introduced into the images that complicate diagnostic analysis
Solution Approach 1:
The patent captures reference spectral data packages of a reference object (such as a white calibration target) before capturing images of the eye. This preliminary reference capture allows the system to later subtract artifacts from the eye images by comparing against the known reference spectrum, thereby eliminating the harmful artifacts while preserving the diagnostic information from the complex optical examination
2Measurement precision
If calibration is performed to remove artifacts, then diagnostic accuracy is improved, but calibration is difficult and costly
Solution Approach 1:
Instead of requiring complex manual calibration procedures, the patent uses a simplified reference object (such as a white calibration target) that can be easily captured and stored as a reference spectral data package. This reference copy is then automatically subtracted from subsequent eye images through computational processing, making calibration simple, automated, and cost-effective while maintaining high diagnostic accuracy
Solution Approach 2:
The system performs self-calibration by automatically capturing reference data and using it to correct its own measurements. The spectral sensor captures reference spectral data packages that are then processed to remove artifacts from eye images without requiring external calibration equipment or manual intervention, thereby simplifying the calibration process and reducing costs
3Measurement precision
If multiple operating characteristics are considered for calibration, then artifact removal accuracy is improved, but the complexity and cost of calibration increases
Solution Approach 1:
The patent extracts and removes only the necessary reference spectral data packages corresponding to specific operating characteristics (such as illumination power levels) from the overall calibration process. By selectively capturing and processing only the reference data needed for each operating condition, the system achieves accurate artifact removal while avoiding the complexity of processing all possible operating characteristic combinations
Data Source
AI summary
A method includes receiving, by one or more processors, operating characteristics at which a spectral sensor was configured while the spectral sensor captured a multi-dimensional spectral data package of a target object. The method, also, includes identifying, by the one or more processors, one or more artifacts caused by the operating characteristics at which the spectral sensor was configured while the spectral sensor captured the multi-dimensional spectral data package of the target object, and generating, by the one or more processors, a calibrated multi-dimensional spectral data package of the target object by removing the one or more artifacts from the multi-dimensional spectral data package of the target object.