Endoscope Image Processing for Stable Lesion Severity Evaluation
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Solution Overview
Problem
Existing endoscope systems struggle to accurately and stably evaluate the progression of lesions in biological tissues due to fluctuations in representative evaluation values based on imaging position and the use of thresholds, leading to subjective and unstable severity calculations.
Innovation Solution
An endoscope processor that calculates lesion severity using a polynomial regression equation adjusting the influence of representative evaluation values based on multiple features and imaging position, integrating pixel evaluation values to provide a stable and accurate severity assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If threshold-based calculation is used to evaluate lesion severity, then the system can provide objective quantification, but the evaluation becomes unstable when representative evaluation values fluctuate around the threshold
Solution Approach 1:
The patent changes the calculation parameter from threshold-based binary classification to polynomial regression-based continuous evaluation. By using a polynomial regression equation that incorporates multiple representative evaluation values (R1, R2, R3) with different weighting coefficients, the system transforms the unstable threshold comparison into a stable continuous function that smoothly evaluates lesion severity without abrupt changes when values fluctuate.
2Reliability
If multiple representative evaluation values are integrated using polynomial regression, then evaluation stability improves, but system complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing multiple representative evaluation values (R1, R2, R3) from different color components before the final severity calculation. These pre-computed values are then integrated using a polynomial regression equation with predetermined weighting coefficients, reducing the complexity of real-time processing while maintaining evaluation stability.
3Measurement precision
If imaging position is considered in severity calculation, then measurement accuracy improves, but calculation complexity increases
Solution Approach 1:
The patent applies local quality by considering the imaging position (entrance side or back side) and applying different polynomial regression equations or weighting coefficients accordingly. The system extracts representative evaluation values specific to each imaging position and uses position-appropriate calculation parameters, allowing accurate local evaluation without requiring a completely complex unified model.
Data Source
AI summary
A processor for an endoscope includes an image processing unit that obtains a severity of a lesion in which a degree of progression is represented by one value, wherein the image processing unit includes a feature amount calculation unit configured to calculate a first pixel evaluation value indicating a degree of a first feature of appearance appearing in a lesion part, a representative value calculation unit configured to calculate a first representative evaluation value by integrating the first pixel evaluation values, and an integration unit configured to adjust an influence degree of the first representative evaluation value indicating a change in the severity with respect to a change in the first representative evaluation value based on information on a color component of an image, and calculate the severity of the lesion based on at least the first representative evaluation value by using the adjusted influence degree.