Fundus Image Enhancement Using Region-Specific CLAHE
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Solution Overview
Problem
Existing image processing techniques for fundus images, such as those disclosed in JP 2008-229157, JP 2017-189530 A, and WO 2019/130583 A1, struggle to effectively sharpen blood vessel regions, making it difficult to accurately analyze and diagnose ocular conditions.
Innovation Solution
An image processing method that converts fundus images from RGB color space to L*a*b* color space, applies Contrast Limited Adaptive Histogram Equalization (CLAHE) with different tile sizes for central and peripheral regions, and enhances lesion portions to improve visibility of blood vessels and lesions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image processing techniques are applied to fundus images, then the overall image can be processed, but the blood vessel regions cannot be sharpened effectively
Solution Approach 1:
The patent divides the fundus image into multiple regions (central region and peripheral region) and applies different processing parameters to each region. The blood vessel regions are specifically segmented and processed with enhanced sharpness parameters, while other regions receive appropriate processing. This segmentation allows targeted sharpening of blood vessels without compromising overall image quality.
Solution Approach 2:
The patent applies different CLAHE processing parameters to different regions of the image. Specifically, the blood vessel regions receive enhanced contrast and sharpness parameters, while the central and peripheral regions receive region-appropriate parameters. This local quality adjustment ensures that blood vessels are sharpened effectively without introducing artifacts or distortion in other areas.
2Ease of operation
If CLAHE processing is applied with uniform parameters across the entire image, then processing is simplified, but the central and peripheral regions cannot be optimized independently
Solution Approach 1:
The patent segments the fundus image into central and peripheral regions, allowing independent parameter optimization for each region. This segmentation enables the system to apply appropriate CLAHE parameters to each region without requiring complex unified processing, maintaining operational simplicity while achieving region-specific optimization.
Solution Approach 2:
The patent implements local quality by applying different CLAHE parameters to central and peripheral regions. The blood vessel regions receive enhanced sharpness and contrast parameters, while other regions receive optimized parameters for their specific characteristics. This local optimization improves blood vessel visibility without unnecessarily complicating the overall processing.
3Area of stationary object
If the imaging field angle is increased to capture more retinal area, then the coverage area is improved, but image quality and sharpness deteriorate
Solution Approach 1:
The patent segments the wide-field fundus image into central and peripheral regions, allowing different sharpness parameters to be applied to each region. This segmentation enables the system to maintain sharpness in the central region (where optical quality is best) while appropriately processing the peripheral region, thus preserving overall image quality despite the wide field of view.
Solution Approach 2:
The patent applies local quality by adjusting CLAHE parameters according to the specific characteristics of each region. The central region receives processing optimized for high sharpness, while the peripheral region receives processing adapted to its lower optical quality. This local optimization allows the system to maintain acceptable image quality across the entire wide field without sacrificing sharpness in the central area.
Data Source
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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.