Endoscope System Fluorescence Color Difference Expansion
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Solution Overview
Problem
It is challenging to visually distinguish between fluorescence regions emitting chemical fluorescence and normal mucous membranes in endoscope systems, especially when the normal mucous membrane has a similar color to the fluorescence region, making it difficult for users to recognize lesions accurately.
Innovation Solution
An endoscope system that includes a light source unit emitting excitation light and reference light across a broad wavelength range, and an image control processor that expands the color difference between normal mucous membranes and fluorescence regions by acquiring color information from fluorescence and reference image signals and processing it in a feature space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If images are always combined and displayed, then visibility of fluorescence region is improved, but frame rate drops
Solution Approach 1:
The system dynamically switches between full combination mode (normal image + fluorescence image) and partial combination mode (only necessary components) based on observation needs, allowing the frame rate to adapt rather than being constantly limited by full combination processing
2Measurement precision
If blue excitation light is used to emit red chemical fluorescence, then fluorescence is excited, but color difference between normal mucous membrane and fluorescence region becomes small
Solution Approach 1:
The system performs color space conversion and chroma saturation enhancement to artificially increase the color difference between fluorescence regions and normal mucous membranes in the displayed image, compensating for the naturally small color contrast when using blue excitation light with red fluorescence emission
3Ease of operation
If normal image and fluorescence image are combined, then user recognition is improved, but processing complexity increases
Solution Approach 1:
The image processing is segmented into separate components (normal image processing, fluorescence image processing, color space conversion, chroma saturation enhancement) that can be independently optimized and controlled, reducing overall processing complexity while maintaining user recognition quality
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
The system enhances the visibility of fluorescence regions by increasing the color difference with normal mucous membranes, allowing for better lesion detection even for users not accustomed to fluorescence observation, while maintaining a frame rate by optimizing image processing.
Implementation Method 1
excitation light, which causes a drug contained in an object to be observed to be excited to emit chemical fluorescence
Implementation Method 2
acquires a plurality of pieces of color information from fluorescence and reference image signals and expands a color difference between a normal mucous membrane and a fluorescence region in a feature space formed by the plurality of pieces of color information
Data Source
AI summary
A light source unit emits excitation light, which causes a drug to be excited to emit chemical fluorescence, and reference light which has a wavelength range from a blue-light wavelength range to a red-light wavelength range. A color information acquisition section acquires a plurality of pieces of color information from fluorescence and reference image signals that are obtained from the image pickup of an object to be observed illuminated with the excitation light and the reference light. A color difference expansion section expands a color difference between a normal mucous membrane and a fluorescence region in a feature space formed by the plurality of pieces of color information.