Choroidal Blood Vessel Diameter Measurement via Segmentation
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Solution Overview
Problem
Existing technologies struggle to accurately measure the diameters of choroidal blood vessels in the eye, which is essential for ophthalmic diagnostics.
Innovation Solution
An image processing method and device that acquire a choroidal vascular image, identify blood vessel center points along the flow direction, and compute the diameter of each blood vessel center point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to visualize choroidal blood vessels, then the blood vessels can be visualized, but the diameters of the blood vessels cannot be accurately measured
Solution Approach 1:
The patent segments the choroidal blood vessel into multiple cross-sectional regions along its length. By dividing the vessel into discrete segments and analyzing each segment independently, the system can accurately measure diameter variations at different locations, resolving the measurement precision problem while managing the complexity of the curved, three-dimensional vessel structure
Solution Approach 2:
The patent transitions from two-dimensional image analysis to three-dimensional spatial analysis by reconstructing the blood vessel's three-dimensional geometry from multiple image planes. This dimensional transformation enables accurate diameter measurement along the vessel's curved path, overcoming the limitations of traditional 2D visualization methods
2Loss of information
If the choroidal vascular image is analyzed to obtain blood vessel diameters, then diagnostic information can be obtained, but the processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by automatically identifying blood vessel center points and establishing reference frameworks before diameter measurement. This preprocessing step simplifies subsequent measurement operations and reduces the complexity of the overall processing system by breaking down the complex task into manageable sequential steps
Solution Approach 2:
The system employs self-service mechanisms through automated algorithms that independently identify blood vessel structures, locate center points, and calculate diameters without requiring manual intervention. This automation reduces operational complexity while ensuring complete and accurate data extraction from the vascular images
Data Source
AI summary
An image processing method, which is executed by a processor, comprises acquiring a choroidal vascular image, identifying, in the choroidal vascular image, a plurality of blood vessel center points of a choroidal blood vessel along a flow direction of the choroidal blood vessel, and computing a blood vessel diameter for each of the plurality of identified blood vessel center points.