Automated Ocular Inflammation Detection Using OCT and Fundus Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for detecting and classifying ophthalmic inflammation, particularly uveitis, are subjective and prone to uncertainty due to reliance on manual examinations, which can be complicated by media opacities like cataracts, limiting accurate grading and effective treatment.
Innovation Solution
The use of automated systems that combine optical coherence tomography (OCT) and fundus imaging to extract characteristic metrics from images, allowing for supervised or unsupervised classification of haze/flare and inflammatory cells, while accounting for lens opacity to improve grading accuracy and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual slit-lamp examination is used for assessing uveitis, then clinical judgment and flexibility are maintained, but subjectivity and uncertainty increase due to reliance on human interpretation
Solution Approach 1:
The patent replaces manual slit-lamp examination with automated image analysis systems that use digital imaging and computer processing to objectively quantify inflammation parameters, eliminating human subjectivity while maintaining clinical assessment capability
Solution Approach 2:
The patent creates digital copies of the eye structures through high-resolution imaging, allowing repeated analysis without exposing the patient to repeated physical examination, and enabling consistent measurement across different observers
2Measurement precision
If manual examination is used, then adaptability to different eye conditions is maintained, but measurement precision deteriorates due to media opacities like cataracts
Solution Approach 1:
The patent divides the eye into distinct anatomical segments (anterior chamber, vitreous, retina) and analyzes each separately using targeted imaging techniques, allowing assessment of inflammation in specific regions without being confounded by media opacities in other regions
Solution Approach 2:
The patent introduces digital image processing as an intermediary between the physical eye structures and the assessment, using algorithms to enhance images and quantify parameters while compensating for the distorting effects of media opacities
3Reliability
If automated image analysis is implemented, then objectivity and grading consistency are improved, but device complexity increases
Solution Approach 1:
The patent integrates multiple functions into a single imaging system that can capture various types of images (fundus photography, OCT, fluorescein angiography) and process them through unified algorithms, reducing the need for separate specialized devices while maintaining comprehensive assessment capability
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
This approach enhances the accuracy and objectivity of uveitis grading, reducing the impact of media opacities and enabling more precise clinical management and therapy development.
Implementation Method 1
Optical Coherence Tomography is a non-invasive, in-vivo imaging technique based on the back-scatter or reflectivity of light in a medium
Implementation Method 2
the image formation process records the back-scattering profile of the light at each location. The amount of scatter is indicative of the reflectivity of the tissue encountered
Data Source
AI summary
Systems and methods to improve the detection and classification of inflammation in the eye are presented. The inflammatory markers in image data can be graded by comparing identified and extracted characteristics from the images with characteristics derived from a set of images of eyes from a general population of subjects. The image data can be divided into sub-regions for analysis to better isolate the true inflammatory markers from the impacts of cataracts or other opacities. In another embodiment, the location of an imaging beam can be controlled to minimize the impact of lens opacities from the collected data used to analyze the inflammation state of an eye.