Image Processing Device for Endoscope Color Space Transformation
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Solution Overview
Problem
Current medical image processing devices have difficulty emphasizing the color difference between normal and abnormal sites, such as atrophic gastric mucosa, leading to challenges in visual recognition and accurate diagnosis.
Innovation Solution
An image processing device that calculates image transformation parameters through congruence transformation to transform colors of a target region in a color image into an achromatic color, allowing for enhanced visualization of subtle hue changes between normal and abnormal sites without altering the distance in the color space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional color space transformation is applied to emphasize color difference between abnormal and normal sites, then color difference enhancement is achieved, but visual recognition accuracy and diagnostic reliability deteriorate
Solution Approach 1:
The patent applies parameter changes by transforming color space coordinates through congruence transformation. Specifically, it changes the chroma component of colors in the color space while maintaining the hue and luminance relationships. This allows the color difference between abnormal and normal sites to be enhanced by adjusting chroma values, thereby improving visual recognition accuracy while maintaining diagnostic reliability through controlled parameter transformation rather than arbitrary color manipulation.
2Measurement precision
If color transformation is applied to render normal mucosa as achromatic color, then boundary identification is improved, but color information loss occurs
Solution Approach 1:
The patent applies local quality by selectively transforming only specific color regions while preserving others. Through congruence transformation in color space, it renders normal mucosa as achromatic color to enhance boundary identification, while preserving the chromatic information of abnormal regions. This localized transformation approach allows boundary identification to be improved without causing complete color information loss, as the transformation is applied selectively based on the specific characteristics of normal versus abnormal tissue regions.
Data Source
AI summary
An image processing device includes: one or more processors including hardware. The one or more processors are configured to: calculate, on a basis of a reference image acquired by capturing an image of a reference subject which has an optical characteristic that is equivalent to at least a part of a living body, image transformation parameters through congruence transformation that transforms a coordinate corresponding to a color of target region included in the reference image defined in a color space into a coordinate corresponding to an achromatic color in the color space; and perform, in the color space on a basis of the calculated image transformation parameters, the congruence transformation of colors of a color image acquired by capturing an image of the living body, the color image being constituted by at least two monochromatic image corresponding to different illumination having different center wavelengths.