Endoscope Focus Control via Area Segmentation and Distance Classification
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Solution Overview
Problem
Endoscope systems with high-pixel image sensors have a shallow depth of field, leading to difficulties in focusing on the intended tissue during procedures due to treatment tools with higher contrast being inadvertently brought into focus, increasing user burden as they must manually designate obstacles frequently changing positions.
Innovation Solution
A focus control device that sets areas in captured images, calculates distance information, and classifies these areas into groups based on object distance, prioritizing focus on groups with sufficient area information to ensure the intended tissue is brought into focus, reducing user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autofocus process is used to achieve deep depth of field, then the user can easily perform diagnosis and treatment, but treatment tools with higher contrast than tissue are inadvertently brought into focus, causing tissue to not be brought into focus
Solution Approach 1:
The patent divides the captured image into multiple areas (e.g., left area, right area, center area) and further classifies them into groups based on distance information. This segmentation allows the system to independently control focus for different spatial regions, preventing treatment tools from blocking the focus on tissue by selectively focusing on tissue areas even when tools are present in the field of view.
Solution Approach 2:
The patent applies different focus control strategies to different areas of the image based on their content and distance characteristics. By determining distance information for each area and classifying areas into groups, the system can selectively bring specific areas into focus while keeping other areas at different focal planes, ensuring tissue remains in focus even when treatment tools are present.
2Manufacturing precision
If manual designation of obstacles is required to maintain focus on tissue, then focus accuracy can be maintained, but user burden increases due to frequent position changes of treatment tools
Solution Approach 1:
The patent implements an automated focus control system that independently identifies and classifies areas based on distance information without requiring user intervention. The system automatically determines which areas to bring into focus by analyzing the captured image and distance data, eliminating the need for users to manually designate obstacles or adjust focus settings frequently.
Solution Approach 2:
The system continuously monitors the captured image and distance information, automatically adjusting focus based on real-time changes in the scene. When treatment tools move position, the system detects these changes through distance information updates and automatically reclassifies areas to maintain proper focus on tissue, providing continuous feedback-based focus adjustment without user input.
3Adaptability or versatility
If treatment tools are present between tissue and imaging device, then treatment can be performed, but contrast difference causes treatment tools to be brought into focus instead of tissue
Solution Approach 1:
The patent segments the image into multiple areas and classifies them into groups based on distance information. This allows the system to distinguish between treatment tools and tissue by their spatial separation and distance characteristics, enabling selective focus on tissue areas even when tools are present in the field of view.
Solution Approach 2:
The patent introduces a distance dimension to the focus control process by calculating distance information for each area and classifying areas into groups based on their distance from the imaging device. This additional dimensional information allows the system to differentiate between objects at different depths, enabling it to focus on tissue even when treatment tools with higher contrast are present at different distances.
Data Source
AI summary
A focus control device includes: a processor including hardware, the processor being configured to implement: an area setting process that sets a plurality of areas to a captured image that has been captured by an imaging section, each of the plurality of areas including a plurality of pixels; an object distance information calculation process that calculates distance information about a distance to an object that is captured within each of the plurality of areas; and a focus control process based on the distance information, wherein the processor implements the focus control process that performs a classification process that classifies the plurality of areas into a plurality of groups, and performs the focus control process based on area information about each of the plurality of groups.