Drusen-Aware Eye Imaging for Macular Degeneration Tracking
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Solution Overview
Problem
Existing vision screening devices are not optimized for detecting and tracking macular degeneration, particularly in identifying soft drusen beneath the retina, leading to inaccurate evaluations and potential undetection of early onset of the condition.
Innovation Solution
A vision screening device equipped with sensors and a controller that captures eye images, identifies regions of interest, detects drusen, and generates alerts or augmented images to track drusen characteristics over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing vision screening devices are used for general vision testing, then basic visual acuity and refractive error testing can be performed, but the ability to detect and track macular degeneration and identify soft drusen is insufficient
Solution Approach 1:
The vision screening device is enhanced with specialized image capture capabilities and processing algorithms that enable it to perform both general vision testing and specialized macular degeneration detection. The device can capture multiple types of eye images (color fundus images, optical coherence tomography scans, fluorescein angiography images) and process them to identify various eye conditions including soft drusen, hard drusen, and other macular abnormalities.
Solution Approach 2:
The device utilizes different imaging parameters and capture modes to detect various characteristics of macular abnormalities. By adjusting imaging parameters such as wavelength, resolution, and capture depth, the device can optimize detection for different types of drusen and macular degeneration stages, enabling accurate identification based on specific visual characteristics.
2Measurement precision
If traditional image capture methods are used, then basic eye imaging can be obtained, but the precision in identifying drusen characteristics and tracking them over time is inadequate
Solution Approach 1:
The image processing system divides the retinal image into multiple regions and analyzes different characteristics separately. The system segments the macular region, identifies drusen based on specific visual characteristics (size, shape, color, texture), and tracks each identified drusen across multiple time points. This segmentation approach enables precise measurement of individual drusen characteristics while managing processing complexity through targeted analysis.
Solution Approach 2:
The system incorporates feedback mechanisms where identified drusen characteristics are stored and compared with previous measurements. The processing system provides feedback by automatically detecting changes in drusen characteristics over time and generating alerts when threshold values are exceeded, enabling continuous monitoring and precise tracking of macular degeneration progression.
3Reliability
If comprehensive macular degeneration tracking is implemented, then early detection and monitoring of drusen can be achieved, but the system complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary actions by capturing baseline images and establishing reference data for normal retinal anatomy before detecting abnormalities. The processing system pre-processes images to enhance relevant features and establishes detection thresholds based on reference data, enabling reliable early detection of macular degeneration while managing system complexity through preparatory processing steps.
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
Enhances the accuracy of macular degeneration detection by monitoring drusen location, size, and characteristics, enabling early detection and tracking of the condition.
Implementation Method 1
Sensors on the device may then collect corresponding light that is reflected by the retinas
Data Source
AI summary
A system includes a vision screening device having at least one sensor. The system also includes a controller operably connected to the at least one sensor. The controller is configured to cause the at least one sensor to obtain an image of an eye, and to identify a region of interest associated with a macula of the eye. The controller is also configured to identify drusen disposed proximate the macula, and to generate an augmented image of the eye. The augmented image includes a component indicating the drusen.