Endoscopic Imaging Subregion Readout for Motion Artifact Reduction
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Solution Overview
Problem
Modern endoscopic imaging systems face challenges in efficiently switching between white light and special light imaging modes, leading to reduced image refresh rates and increased motion artifacts, especially when detecting predefined structures like intestinal polyps or bleeding, due to the limitations of CMOS image sensors and the need for high light sensitivity in special light imaging modes.
Innovation Solution
An endoscopic imaging method that utilizes CMOS image sensors to capture and process subregions of interest (ROI) in white light images, allowing for real-time detection of predefined structures and automatic switching to special light imaging modes, which increases image refresh rates and reduces noise by reading out only the necessary subregion data, enabling higher sensitivity and reduced motion artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire CMOS image sensor is read out in special light imaging mode, then complete image data is obtained, but the image refresh rate is reduced and motion artifacts increase
Solution Approach 1:
The image sensor is divided into multiple subregions, and only the subregion containing the detected structure is read out in special light imaging mode. This segmentation allows the system to maintain high image refresh rates by reading out only the necessary portion of the sensor, while still capturing complete data for the area of interest.
Solution Approach 2:
The system applies different readout strategies to different regions of the image sensor. The subregion containing the detected structure receives high-quality special light imaging with focused readout, while other regions are not read out during special light imaging. This local quality approach optimizes the balance between data completeness and refresh rate.
2Measurement precision
If special light imaging mode is activated for the entire image, then comprehensive structure detection is achieved, but noise increases and sensitivity is reduced
Solution Approach 1:
The system extracts only the necessary subregion containing the detected structure from the full image sensor for special light imaging readout. This extraction eliminates the need to read out and process noise-containing data from unrelated regions, thereby reducing overall image noise while maintaining sensitivity for the area of interest.
Solution Approach 2:
Instead of applying special light imaging to the entire sensor, the system applies it partially only to the subregion containing the detected structure. This partial action reduces the accumulation of noise from unrelated areas while maintaining sufficient imaging quality for structure detection and analysis.
3Device complexity
If the image refresh rate is halved when switching between white light and special light modes, then processing load is reduced, but motion artifacts increase
Solution Approach 1:
By segmenting the image sensor into subregions and reading out only the relevant subregion during special light imaging, the system maintains high image refresh rates without significantly increasing processing load. The reduced data volume from subregion readout keeps processing manageable while preventing motion artifacts.
Solution Approach 2:
The system implements periodic switching between white light imaging (for structure detection) and special light imaging (for detailed analysis), with the subregion readout approach enabling frequent transitions without motion artifacts. This periodic action maintains both processing efficiency and image quality.
Data Source
AI summary
A method for endoscopic imaging including: capturing white light images with a video endoscope under white light illumination; evaluating the captured white light images for a structure having a predefined characteristic, when the presence of the structure having the predefined characteristic is found in a white light image, setting a special light imaging mode in which a light source generates special light illumination using the at least one special light and one or more images of a video stream are captured under the special light illumination and subjected to image processing in the set special light processing mode; identifying a subregion of the at least one white light image that contains the structure with the predefined characteristic and reading out only the subregion of a CMOS image sensor associated with the video endoscope, and processing the image data read out from the subregion as one or more special light images.