Vitreous Opacity Quantification via Infrared Imaging Analysis
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Solution Overview
Problem
Current methods lack a reliable and efficient way to quantify the severity of visual obstruction caused by opacities in the vitreous of the eye, such as floaters, which can vary in impact on vision and require tailored treatment approaches.
Innovation Solution
An ophthalmological diagnostic device and method utilizing image analysis systems with infrared imaging and scanning laser ophthalmoscopes to detect and quantify opacity areas within the visual axis, combined with video analysis to assess obstruction over time, and a projector to evaluate reading proficiency and obstruction during controlled eye movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging methods are used to assess vitreous opacity, then the assessment process is simple, but the measurement precision and reliability of quantification are insufficient
Solution Approach 1:
The vitreous cavity is divided into multiple depth layers through optical coherence tomography imaging, allowing opacities to be segmented and quantified at different depths. This segmentation enables precise measurement of opacity cross-sectional areas at specific locations along the visual axis, directly improving measurement precision while managing system complexity through structured data organization.
Solution Approach 2:
The patent replaces subjective manual assessment with automated image analysis algorithms that objectively quantify opacity characteristics. The system uses computer-based processing to calculate opacity cross-sectional areas, obstruction percentages, and severity scores, eliminating human subjectivity and significantly improving measurement precision and reliability.
2Reliability
If static imaging is used to assess opacity, then the examination time is short, but the ability to capture dynamic changes in opacity impact on vision is limited
Solution Approach 1:
The system performs repeated imaging acquisitions at different time points during a single examination session, capturing the dynamic movement of vitreous opacities as the patient moves their eye. This periodic sampling through video-rate imaging allows the system to calculate temporal averages and assess how opacities dynamically obstruct the visual axis, significantly improving assessment reliability.
Solution Approach 2:
The patent implements continuous video-rate imaging that captures opacity dynamics throughout the entire examination period rather than relying on discrete static snapshots. This continuous acquisition ensures that transient obstructions and moving opacities are captured, providing a more reliable and comprehensive assessment of visual impact over time.
3Measurement precision
If comprehensive video analysis is performed to assess dynamic obstruction, then the measurement precision improves, but the processing time and complexity increase
Solution Approach 1:
The system performs preliminary processing of video frames by identifying and tracking opacity regions across multiple frames before final quantification. Pre-processing steps include noise reduction, opacity segmentation, and feature extraction that prepare data for efficient final analysis, reducing the computational burden of comprehensive video analysis while maintaining measurement precision.
Solution Approach 2:
The patent implements a multi-level analysis approach where the system first performs rapid screening of video frames to identify frames with significant opacity obstruction, then applies detailed quantitative analysis only to those critical frames. This selective processing maintains high measurement precision for obstruction quantification while significantly improving processing efficiency by avoiding exhaustive analysis of all frames.
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
Enables accurate and repeatable quantification of opacity-induced visual obstruction, allowing for appropriate treatment decisions based on dynamic changes in opacity impact on vision.
Implementation Method 1
utilizing image analysis systems with infrared imaging and scanning laser ophthalmoscopes to detect and quantify opacity areas
Implementation Method 2
utilizing image analysis systems with infrared imaging and scanning laser ophthalmoscopes to detect and quantify opacity areas
Data Source
AI summary
Examples of devices and method for quantifying opacities in an eye are shown. Examples include analysis of still images or video images. In one example a cross section area of opacities within a visual axis are quantified. Opacities in the vitreous of an eye, such as “floaters” can vary in severity from little or no reduction in vision, to bothersome, to high reduction in visual function. It is desirable to be able to quantify a level of severity of visual obstruction within a patient's eye and proceed with a level of treatment to match the condition.