Regional CLAHE Processing for Fundus Vessel and Lesion Visibility
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Solution Overview
Problem
Existing image processing techniques for fundus images, such as those disclosed in Japanese Patent Application Laid-Open (JP-A) No. 2008-229157, struggle to effectively sharpen both the central and peripheral regions of the fundus image, leading to suboptimal visibility of blood vessels and lesions.
Innovation Solution
A method and device that perform distinct enhancement processing on the central and peripheral regions of a fundus image using different parameters, specifically through Contrast Limited Adaptive Histogram Equalization (CLAHE) with tailored tile sizes, enhancing the central region with a first parameter and the peripheral region with a second parameter to account for distortion and improve image sharpness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a single enhancement processing is applied to the entire fundus image, then the processing is simple and fast, but the sharpness and visibility of blood vessels and lesions are insufficient in both central and peripheral regions
Solution Approach 1:
The fundus image is divided into a central region and a peripheral region, with each region processed using different enhancement parameters. The central region uses first enhancement parameters optimized for its characteristics, while the peripheral region uses second enhancement parameters tailored to its specific properties, thereby achieving region-specific sharpness improvement without applying a one-size-fits-all approach
Solution Approach 2:
Different enhancement parameters are applied to different regions of the fundus image based on their local characteristics. The central region receives processing with first parameters (e.g., first tile size for CLAHE) while the peripheral region receives processing with second parameters (e.g., second tile size), allowing each region to be optimized independently for its specific visual requirements
2Measurement precision
If enhancement processing is applied to improve visibility of blood vessels and lesions, then diagnostic accuracy improves, but processing time increases
Solution Approach 1:
The image is segmented into central and peripheral regions, allowing parallel processing with region-specific parameters. This segmentation enables the system to apply appropriate enhancement strength to each region without unnecessarily processing the entire image with high-computation parameters, thus improving detection accuracy while controlling processing time
Solution Approach 2:
The enhancement parameters (such as tile sizes in CLAHE) are changed according to the region being processed. By using different parameters for central and peripheral regions, the system optimizes the balance between enhancement effectiveness and processing speed for each region, avoiding the time penalty of applying maximum enhancement uniformly across the entire image
Data Source
AI summary
An image processing method, including: by a processor: acquiring a fundus image; performing a first enhancement processing on an image of at least a central region of the fundus image, and performing a second enhancement processing, which is different from the first enhancement processing, on an image of at least a peripheral region of the fundus image that is at a periphery of the central region; and generating an enhanced image of the fundus image on the basis of a first image obtained as a result of the first enhancement processing having been performed and a second image obtained as a result of the second enhancement processing having been performed.