Endoscope Illumination Control for Fluid Visibility
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Solution Overview
Problem
Endoscope systems face challenges in maintaining visibility during underwater or fluid-filled observations due to spectral and scattering characteristics of the fluid, which reduces image quality and contrast, especially with the presence of blood or tissue fragments, as existing methods do not effectively adjust illumination to compensate for these factors.
Innovation Solution
An endoscope system with a processor-controlled illumination system that determines the presence of fluid and adjusts the illumination mode by switching between different light spectra, increasing long wavelength components to improve visibility through fluid-filled environments, using multiple light sources and machine learning for optimal spectrum control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional illumination is used in fluid-filled environments, then the illumination system remains simple, but image quality and contrast deteriorate due to spectral and scattering characteristics of the fluid
Solution Approach 1:
The illumination system dynamically switches between different observation modes (first observation mode without fluid, second observation mode with fluid) based on detected fluid presence. This dynamic adaptation allows the system to optimize illumination spectra for each condition, improving image quality while maintaining manageable complexity through automated mode selection rather than continuous manual adjustment.
Solution Approach 2:
The system changes the spectral parameters of illumination light by selecting different illumination modes with distinct spectral characteristics. The first illumination mode uses spectra suitable for air environments, while the second illumination mode uses spectra optimized for fluid-filled environments, particularly emphasizing long wavelength components to penetrate fluid and reduce scattering effects, thereby improving image quality.
2Reliability
If illumination spectra are not adjusted for fluid presence, then the control system remains simple, but visibility and image contrast worsen in fluid-filled environments
Solution Approach 1:
The system incorporates feedback mechanisms that detect the presence of fluid in the observation region and automatically trigger appropriate illumination mode switching. This feedback loop ensures reliable visibility by continuously monitoring environmental conditions and adapting illumination spectra accordingly, while the automation reduces the complexity of manual control interventions.
Solution Approach 2:
The control system dynamically adapts illumination parameters based on real-time detection of fluid presence. By switching between predetermined illumination modes rather than requiring continuous manual adjustment, the system achieves reliable visibility in varying conditions while keeping the control system complexity manageable through automated decision-making algorithms.
3Manufacturing precision
If standard illumination is used regardless of fluid presence, then the device operation remains simple, but image clarity and contrast deteriorate
Solution Approach 1:
The illumination system performs self-service by automatically detecting fluid presence and selecting appropriate illumination modes without requiring manual intervention. The system serves itself by using its own detection capabilities to trigger the correct illumination spectrum, thereby maintaining image clarity while preserving ease of operation through automated rather than manual control.
Solution Approach 2:
The system dynamically adjusts illumination spectra based on detected environmental conditions, switching between first and second observation modes as needed. This dynamic behavior automatically optimizes image clarity for each condition while maintaining ease of operation, as the system adapts itself rather than requiring the operator to manually adjust complex illumination parameters.
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 image clarity and contrast by adapting illumination spectra based on fluid presence and transparency, effectively improving visibility of objects within fluid-filled environments, even in conditions with blood or tissue fragments, by increasing long wavelength components and using machine learning for optimized light control.
Implementation Method 1
an image sensor that captures an image of an object toward which the illumination light is emitted; and a processor, the processor being configured to perform: determining whether a fluid is present in the object
Implementation Method 2
in a case where the fluid is present in the object, switching to a second observation mode in which to illuminate the object by second illumination light, wherein the second illumination light is larger than the first illumination light in a relative ratio of long wavelength components
Implementation Method 3
an image sensor that captures an image of an object toward which the illumination light is emitted
Data Source
AI summary
An endoscope system includes a light source that emits illumination light, an image sensor that captures an image of an object toward which the illumination light is emitted, and a processor. The processor is configured to determine whether a fluid is present in the object. If the fluid is not present in the object, the processor switches to a first observation mode in which to illuminate the object by first illumination light. If the fluid is present in the object, the processor switches to a second observation mode in which to illuminate the object by second illumination light. The second illumination light includes is larger than the first illumination light in a relative ratio of long wavelength components.