Beam-Splitter Fluorescence Imaging for Corneal Infection Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional diagnosis of bacterial and fungal infections of the cornea, such as microbial keratitis, is challenging due to the high cost and inaccessibility of laboratory techniques, and requires specialist training, which can lead to delayed diagnosis and increased healthcare costs.
Innovation Solution
A low-cost, portable fluorescence-based imaging device using a UV light source and dual-image sensors with beam splitters and filters to capture fluorescence emissions from NADH and FAD, enabling rapid identification and classification of bacterial and fungal infections by calculating a spectral luminescence intensity ratio (SLIR) without specialist training.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional laboratory techniques are used for diagnosis, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces complex mechanical laboratory techniques with an optical fluorescence-based imaging system. The system uses UV light excitation, fluorescence emission detection, and image processing to identify microbial infections, substituting traditional mechanical laboratory methods with a more accessible optical approach while maintaining diagnostic accuracy
Solution Approach 2:
The patent changes the diagnostic approach by measuring fluorescence intensity ratios (such as NADH/FAD ratios) at specific wavelengths instead of using traditional laboratory methods. This parameter-based optical measurement enables accurate microbial identification through spectral analysis without requiring complex laboratory infrastructure
2Measurement precision
If specialist training is required for diagnosis, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system incorporates automated image processing and analysis algorithms that automatically interpret fluorescence images and provide diagnostic results. The processor calculates fluorescence intensity ratios, compares them against reference values, and identifies microbial infections without requiring specialist intervention, enabling non-specialists to perform accurate diagnoses
Solution Approach 2:
The patent replaces the need for specialist expertise with an automated optical imaging and image processing system. The device captures fluorescence images, processes them through algorithms, and provides diagnostic output automatically, substituting human specialist analysis with automated computational methods that are accessible to non-specialists
3Measurement precision
If conventional diagnosis methods are used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary action by capturing fluorescence images and processing them immediately at the point of care. The automated image processing and analysis occur in real-time or near-real-time, providing rapid diagnostic results without the need for sample transport or waiting for laboratory analysis, thus reducing diagnosis time while maintaining accuracy
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
The device provides rapid, accurate, and non-invasive diagnosis of corneal infections, allowing non-specialists to identify the presence and severity of infections, reducing healthcare costs and improving patient outcomes through accessible and efficient microbial keratitis detection.
Implementation Method 1
capture fluorescence emissions from NADH and FAD
Implementation Method 2
UV light source and dual-image sensors with beam splitters and filters to capture fluorescence emissions
Implementation Method 3
beam splitters and filters to capture fluorescence emissions
Implementation Method 4
first beam splitter positioned at an intersection of the aperture axis and the source axis, and a second beam splitter positioned at an intersection of the first imaging axis and the second imaging axis
Data Source
AI summary
A device for two, or more, color fluorescence imaging and methods for fluorescence-based corneal infection imaging. The device includes a frame including an aperture defining an aperture axis, and an imaging lens aligned with the aperture axis. A first image sensor with a first imaging axis aligned with the aperture axis and a second image sensor with a second imaging axis. The device includes a light source configured to emit a light along a source axis, a first beam splitter positioned at an intersection of the aperture axis and the source axis; and a second beam splitter positioned at an intersection of the first imaging axis and the second imaging axis.