Fundus Image Comparison for Diabetic Retinopathy Progression Prediction
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Solution Overview
Problem
Diabetic retinopathy progression is challenging to monitor effectively due to inconvenient periodic eye examinations and a shortage of qualified healthcare professionals, particularly in rural areas, leading to potential serious visual acuity decline.
Innovation Solution
A system and method utilizing an image-capturing module and processing unit to capture and compare fundus images over time, indicating differences and predicting diabetic retinopathy progression, which includes a data server with integrated units for image registration, analysis, warning, communication, and processing, enabling remote monitoring and prediction of retinal health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If periodic eye examinations are performed by health care professionals, then diabetic retinopathy can be detected early, but it is inconvenient for patients due to time constraints and there is a shortage of qualified professionals
Solution Approach 1:
The system enables patients to perform self-monitoring of their retinal health by capturing fundus images using a mobile device camera and processing unit, eliminating the need for frequent visits to healthcare professionals while maintaining reliable detection capability
Solution Approach 2:
An automated image processing system acts as an intermediary between the patient and healthcare professional, performing preliminary analysis of fundus images to detect diabetic retinopathy, thereby reducing the burden on both patients and professionals
2Measurement precision
If healthcare professionals perform eye examinations, then accurate diagnosis can be made, but there is a huge unmet need for qualified professionals especially in rural areas
Solution Approach 1:
The patent replaces the mechanical system of manual examination by healthcare professionals with an automated image processing system that uses computer algorithms to analyze fundus images, enabling accurate diagnosis without requiring specialized human expertise at every location
Solution Approach 2:
The system captures digital copies of fundus images using a mobile device camera and processes them through an automated analysis system, allowing accurate diagnosis to be performed remotely without requiring the physical presence of qualified professionals
3Ease of operation
If diabetic retinopathy progression is not well monitored, then visual acuity can be preserved without frequent examinations, but serious decline in visual acuity may occur
Solution Approach 1:
The system performs periodic automated analysis of fundus images at different time points, comparing baseline images with subsequent images to detect progression of diabetic retinopathy, maintaining reliable monitoring while reducing the frequency of patient visits
Solution Approach 2:
The system provides feedback by comparing current fundus images with baseline images and detecting changes indicative of retinopathy progression, enabling continuous monitoring without frequent examinations through automated image analysis and comparison
Data Source
AI summary
The present disclosure provides a system for predicting diabetic retinopathy progression. The system includes an image-capturing module and a processing unit. The image-capturing module is configured to capture a first fundus image of a user at a first time and a second fundus image of the user at a second time different from the first time. The processing unit is configured to receive the first fundus image and the second fundus image, compare the first fundus image and the second fundus image and indicate a difference between the first fundus image and the second fundus image. The processing unit is also configured to provide a prediction in a diabetic retinopathy progression of the user based on the difference. A method for predicting diabetic retinopathy progression is also provided in the present disclosure.