Endoscopic Image Processing for Visibility-Guided Light Switching
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Solution Overview
Problem
Existing endoscopic systems struggle to effectively integrate and display normal and special light images together, often requiring manual switching between them, which can lead to suboptimal visibility and inefficient lesion detection.
Innovation Solution
An endoscopic image processing device that acquires and processes both normal and special light images, determines visibility thresholds for each, and provides notification information to guide the user based on visibility levels, allowing seamless integration and improved lesion detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual switching between normal light image and special light image is implemented, then the system structure remains simple, but the operation efficiency and lesion detection accuracy deteriorate due to suboptimal visibility
Solution Approach 1:
The system automatically determines visibility of lesion candidate regions and switches between normal light and special light images without manual intervention. The processor autonomously evaluates visibility metrics and selects the appropriate image type, enabling the system to serve itself rather than requiring operator control for each switching decision.
Solution Approach 2:
The system changes the imaging parameter (light type) dynamically based on visibility assessment. When the processor determines that special light provides better visibility for a lesion candidate region, it automatically switches to display the special light image, optimizing the parameter selection based on real-time evaluation rather than fixed manual settings.
2Measurement precision
If automatic switching between normal and special light images is implemented, then visibility and detection accuracy improve, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system performs preliminary visibility assessment on both normal light and special light images before final display selection. The processor pre-evaluates the visibility of lesion candidate regions in both image types and prepares the optimal image in advance, ensuring high detection accuracy without requiring complex real-time switching mechanisms during observation.
Solution Approach 2:
The processor acts as an intermediary that automatically compares visibility metrics between normal light and special light images. It mediates the selection process by evaluating which image type provides superior lesion visibility and automatically presenting the optimal image to the operator, eliminating the need for manual comparison and switching while maintaining high detection accuracy.
3Loss of information
If both normal light image and special light image are displayed simultaneously, then comprehensive information is provided, but the ease of operation deteriorates due to information overload
Solution Approach 1:
The system extracts and displays only the most relevant image type based on lesion visibility assessment. Rather than showing both normal light and special light images simultaneously, the processor evaluates which image provides better lesion visibility and extracts that specific view for display, preventing information overload while maintaining complete diagnostic information.
Solution Approach 2:
The display content dynamically adapts based on real-time visibility assessment. The system transitions between displaying normal light images and special light images according to which type provides superior lesion visibility in each region, creating a dynamic display that optimizes information presentation without overwhelming the operator with static simultaneous views of both image types.
Data Source
AI summary
One or more processors create a first image from a first signal, create a second image from a second signal, determine whether visibility of at least a part of the second image is equal to or higher than a second threshold, or lower than the second threshold, and create different notification information depending on a result of the determination of the visibility. The one or more processors create at least one kind of: the notification information for guiding to the second image when the visibility is equal to or higher than the second threshold; or the notification information for notifying that the second image is not suitable for viewing when the visibility is lower than the second threshold.