Lifeform Image Color Standardization for Tissue Analysis
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Solution Overview
Problem
Lifeform images can vary significantly in color due to differences in image capture devices and staining methods, leading to reduced accuracy in tissue extraction and analysis.
Innovation Solution
A lifeform image analysis system that includes an image input module, structure extraction module, color computation module, and color distribution conversion module, which standardizes the color distribution of lifeform images by comparing them to stored standard colors and adjusting the image to match these standards, thereby reducing color differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is performed without color distribution conversion, then the analysis process is simple and fast, but the analysis accuracy deteriorates due to color variations from different capture devices and staining methods
Solution Approach 1:
The patent applies preliminary action by performing color distribution conversion before tissue extraction analysis. The system pre-processes the lifeform image by converting its color distribution to match a standard color distribution, ensuring that color variations from different capture devices and staining methods do not affect subsequent analysis accuracy. This preliminary standardization step resolves the contradiction by preparing the image in advance, so that accurate analysis can be performed without requiring complex real-time color correction during the analysis process.
2Reliability
If color distribution conversion is applied to all images, then analysis accuracy is improved across different imaging conditions, but processing time and computational resources increase
Solution Approach 1:
The patent applies parameter changes by transforming the color distribution parameters of the lifeform image to match standard color distribution parameters. The color distribution conversion means changes the color parameters (such as mean color, standard deviation, and higher-order moments) of the input image to correspond to predetermined standard values. This approach ensures reliable and consistent analysis results across different imaging conditions while maintaining efficient processing by using mathematical parameter transformation rather than complex pixel-by-pixel processing.
3Measurement precision
If standard color values are stored and used for conversion, then color standardization is achieved, but the system becomes more complex requiring storage and retrieval mechanisms
Solution Approach 1:
The patent applies copying by creating a standardized color distribution model that represents ideal color characteristics for lifeform images. Instead of storing numerous reference images, the system stores standard color distribution parameters (mean, standard deviation, and higher-order moments) that can be copied and applied to any input image. This copying approach achieves accurate color standardization while keeping the system structure relatively simple, as it requires storing only numerical parameters rather than large image datasets.
Data Source
AI summary
A image input means 81 inputs a lifeform image which is a captured image of a lifeform sample. A structure standard color storage means 82 stores a standard color of a structure included in the lifeform image. A structure extraction means 83 extracts a target structure from the lifeform image. A structure color computation means 84 computes, from an image of the structure extracted by the structure extraction means 83, a color of the structure. A color distribution conversion means 85 converts a color distribution of the input lifeform image so that a difference between the color of the structure computed by the structure color computation means 84 and the standard color of the corresponding structure stored in the structure standard color storage means 82 is reduced.