Ocular Image Merging for Glaucoma Progression Analysis
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Solution Overview
Problem
Current methods for diagnosing glaucoma, such as OCT, struggle to effectively assess the spatial relationship between the optic disc and macula for disease progression due to separate imaging and analysis of these areas.
Innovation Solution
A device and method that combine ocular images from various areas by generating comparison images based on optic nerve thickness and blood vessel matching, creating a combined image to visualize eye disease progression, and analyzing this progression using pre-stored images and prone area information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If separate imaging and analysis of optic disc and macula are performed, then imaging simplicity is maintained, but the ability to grasp spatial relationship and disease progression is degraded
Solution Approach 1:
The patent combines separate ocular images (optic disc and macula) into a single composite ocular image that preserves the spatial relationship between these structures. This merging allows comprehensive analysis of disease progression while maintaining the simplicity of separate imaging acquisition.
2Measurement precision
If multiple ocular images from various areas are combined, then comprehensive disease progression analysis is improved, but image processing complexity increases
Solution Approach 1:
The patent segments the ocular image into multiple regions (optic disc, macula, and other areas) with distinct characteristics. Each region is processed independently to extract relevant features, and then these segmented regions are combined to form a comprehensive analysis, reducing overall processing complexity while maintaining precision.
Solution Approach 2:
The patent applies different processing methods to different regions of the ocular image based on their specific characteristics. For example, optic nerve fiber layer analysis is performed on the optic disc region while retinal layer analysis is performed on the macula region, optimizing measurement precision for each area without uniformly increasing overall complexity.
Data Source
AI summary
The present invention relates to a method and a device for determining structural progression of an eye disease using an ocular image. According to an embodiment of the present invention, a device for determining structural progression of an eye disease includes a processor, and a memory electrically connected to the processor, wherein, when the processor is executed, the memory stores instructions for obtaining a first-nth ocular image, which is an nth first ocular image for a user (where n is a natural number), obtaining a second-nth ocular image, which is an nth second ocular image for the user, combining the first-nth ocular image and the second-nth ocular image according to a preset method to generate an nth combined image, and generating an nth eye disease image for the user by using the nth combined image and a preset prone area image.