Fundus Analyzing Apparatus Drusen Detection via Pigment Layer Protrusion
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Solution Overview
Problem
Current fundus imaging techniques, particularly for age-related macular degeneration diagnosis, struggle to detect small drusen due to subtle differences in color and brightness, making early detection and accurate distribution assessment challenging.
Innovation Solution
A fundus analyzing apparatus and method that identifies the pigment layer region in tomographic images, calculates a convex curve based on the layer region's shape, and identifies protrusion regions where the layer region deviates from the expected curve, generating morphological information to detect even small drusen effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fundus imaging techniques are used to detect drusen, then the imaging process is simple, but small drusen cannot be detected due to subtle differences in color and brightness
Solution Approach 1:
The patent transitions from two-dimensional fundus surface imaging to three-dimensional tomographic imaging by adding the depth dimension (z-direction). This enables detection of drusen based on their three-dimensional morphological characteristics and protrusion from the retinal surface, rather than relying solely on subtle color and brightness differences in flat images.
Solution Approach 2:
The patent segments the fundus imaging into multiple depth layers through tomographic scanning. By dividing the imaging space into discrete depth intervals and reconstructing cross-sectional images at different depths, small drusen can be identified by their characteristic protrusion patterns across multiple layers, enhancing detection precision.
2Measurement precision
If three-dimensional tomographic images are acquired by scanning in both horizontal and vertical directions, then drusen distribution can be assessed, but the scanning time and measurement duration increase
Solution Approach 1:
The patent employs periodic scanning patterns where the light beam systematically moves through horizontal and vertical directions in repeated cycles. This structured periodic scanning covers the entire measurement region while optimizing the measurement time by efficiently sampling the fundus surface and reconstructing three-dimensional information from the periodic scan data.
Solution Approach 2:
The patent performs preliminary scanning to acquire rough three-dimensional topography data before detailed drusen analysis. This preliminary action establishes the overall fundus landscape and identifies regions of interest, allowing subsequent focused scanning to reduce total measurement time while maintaining assessment 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
Enables the precise detection of small drusen and their distribution by characterizing protrusion regions in the pigment layer, facilitating early diagnosis and treatment of age-related macular degeneration.
Implementation Method 1
superposes the reflected light and the reference light to generate an interference light
Implementation Method 2
acquires the spectral intensity distribution of the interference light to execute Fourier transform, thereby imaging the morphology in the depth direction
Implementation Method 3
acquiring the spectral intensity distribution based on an interference light obtained by superposing the reflected lights of the light of the respective wavelengths on the reference light, and executing Fourier transform
Data Source
AI summary
A fundus analyzing apparatus 1 performs OCT measurements of a fundus Ef and generates multiple tomographic images that each depict layer structures of the fundus Ef. Each formed tomographic image is stored in a storage 212. Based on the pixel values of the pixels of each tomographic image, the layer-region identifying part 233 identifies the layer region corresponding to the pigment layer of the retina. Based on the shape of the layer region, the curve calculator 234 obtains a convex standard curve in the direction of depth of the fundus Ef. Based on the layer region and the standard curve, a protrusion-region identifying part 235 identifies protrusion regions where the layer region protrudes in the opposite direction from the direction of depth of the fundus Ef. A morphological-information generating part 236 generates morphological information representing the morphology (number, size, distribution, etc.) of the protrusion regions.