Image Processing Device for Cell Type Distinction
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Solution Overview
Problem
Current methods for distinguishing between different types of cells in color images are indirect and struggle to explicitly clarify the small color differences, making accurate diagnosis challenging.
Innovation Solution
An image processing device and program that analyze and modify the hue, saturation, and intensity of pixels in a color image to maximize the distance between target pixels in a color space, allowing for clearer differentiation of cell types based on color differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If color difference for each kind of cells is distinguished based on the sub-volume in the color space (indirect method), then it is possible to identify cell types, but the method cannot explicitly distinguish the color difference in real images and requires complex processing
Solution Approach 1:
The patent applies color space transformation by converting RGB images to L*a*b* color space, where the a* and b* channels represent color differences. This transformation enables explicit visualization of subtle color variations between cell types that are not apparent in the original RGB image, directly resolving the contradiction by making color differences visible while maintaining processing simplicity
Solution Approach 2:
The patent extracts color information from the L*a*b* color space and plots it in a two-dimensional color difference plane (a* vs b*). This dimensional transformation from three-dimensional color space to a two-dimensional projection allows explicit distinction of cell types based on their color characteristics, solving the problem of invisible color differences in real images
2Measurement precision
If manual observation by technical experts is used to diagnose cell types, then accurate diagnosis can be made based on experience, but the process is time-consuming and requires high magnification imaging
Solution Approach 1:
The patent replaces manual expert observation with an automated image processing system that uses color space transformation and analysis. The system automatically extracts color features from L*a*b* color space and identifies cell types through algorithmic processing, eliminating the need for manual microscopic examination while maintaining diagnostic accuracy and significantly reducing time consumption
Solution Approach 2:
The patent transforms the diagnostic approach by changing from analyzing morphological parameters (cell shape, size) to analyzing color parameters (a* and b* values in L*a*b* space). This parameter transformation enables automated distinction of cell types based on color differences alone, making the process both faster and more objective while preserving diagnostic accuracy
Data Source
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AI summary
An inspection apparatus includes an imaging device and an image processing device. The imaging device photographs a specimen and outputs a color image of the specimen to the image processing device. The image processing device, after subjecting the color image of the specimen to negative-positive reversal, finds a hue of each pixel of the color image having been subjected to negative-positive reversal. After detecting a mode value of the hue from the hue of each pixel of the color image having been subjected to negative-positive reversal, the image processing device changes the hue of each pixel of the color image in accordance with a difference between a boundary value of two predefined hues and the detected mode value. In accordance with the change of the hue, a plurality of target pixels different in the saturation is extracted and the saturation and the intensity of each pixel are changed, or the gradation of each pixel is converted so that the plurality of target pixels becomes most distant from one another in a color space.