Endoscope Processor Oxygen Saturation Artifact Correction
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Solution Overview
Problem
Existing endoscope systems face challenges in accurately calculating oxygen saturation of blood hemoglobin due to factors other than blood hemoglobin, such as dirt or artifacts, leading to reduced calculation accuracy and errors in oxygen saturation images.
Innovation Solution
An endoscope system with a processor device that adjusts threshold values based on exposure amount designation values and generates oxygen saturation images by distinguishing between regions with reliable and unreliable oxygen saturation data, using specific colors to indicate unreliable regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the distal end of the endoscope is brought close to the observation target, then the imaging brightness and color consistency are improved, but the oxygen saturation calculation accuracy deteriorates due to pixel saturation and artifacts
Solution Approach 1:
The image is divided into multiple regions based on pixel value characteristics. Regions with pixel values indicating potential artifacts or saturation are segmented and treated differently from regions with reliable oxygen saturation data, allowing selective processing to maintain overall image quality while correcting local errors
Solution Approach 2:
Different processing methods are applied to different regions of the image. Regions identified as having artifacts or saturation errors receive correction processing, while regions with reliable data maintain their original characteristics, ensuring local optimization without affecting the entire image
2Stability of the object's composition
If automatic exposure adjustment is performed to prevent pixel saturation, then the imaging consistency is improved, but the oxygen saturation calculation accuracy deteriorates due to exposure-related artifacts
Solution Approach 1:
The system calculates oxygen saturation values and reliability indicators for each pixel, then uses this feedback to identify regions where exposure adjustment has introduced artifacts. This feedback loop enables selective correction of affected regions while preserving the benefits of automatic exposure control for the overall image
Solution Approach 2:
The system performs preliminary identification of regions with potential exposure-related artifacts before final oxygen saturation display. By pre-processing the image data to flag problematic regions, the system can apply corrections in advance, ensuring accurate oxygen saturation calculation throughout the imaging process
3Productivity
If the signal ratio is used to calculate oxygen saturation, then the calculation speed is improved, but the calculation accuracy deteriorates when factors other than blood hemoglobin change the signal ratio
Solution Approach 1:
A reliability indicator is introduced as an intermediary parameter between the signal ratio and the final oxygen saturation value. This intermediary helps distinguish between signal ratio changes caused by blood hemoglobin and those caused by other factors such as dirt or artifacts, enabling accurate oxygen saturation calculation even when using rapid signal ratio methods
Solution Approach 2:
The system monitors changes in pixel values and signal ratios to detect when factors other than blood hemoglobin are affecting the measurement. By detecting these parameter changes, the system can identify and correct erroneous regions while maintaining the fast calculation speed of signal ratio-based methods for valid regions
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 effectively calculates oxygen saturation and identifies regions of error in the image, providing accurate oxygen saturation information even when artifacts or dirt are present, ensuring reliable imaging results.
Implementation Method 1
an imaging device configured to image the observation target with reflected light of the illumination light
Implementation Method 2
a wavelength range where an absorption coefficient changes according to oxygen saturation of blood hemoglobin
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
An exposure amount designation value calculation unit calculates an exposure amount designation value for designating the amount of exposure, which is required to image an observation target, based on an image signal. A threshold value calculation unit calculates a threshold value for comparison with the pixel value of the image signal according to the exposure amount designation value. A region detection unit detects a first region, in which the pixel value falls within a range set by the threshold value, and a second region, in which the pixel value is out of the range. An image generation unit generates an oxygen saturation image, in which the oxygen saturation is displayed differently in the first and second regions, using the image signal, the oxygen saturation, and information of the first and second regions.