Immunoreagent Card Image Analysis for Weak Positive Detection
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Solution Overview
Problem
Current methods for reading immunoreagent card results, especially weak positives, are prone to misjudgment due to low color rendering and require significant manpower, leading to uncertainty and inefficiency in large-scale testing.
Innovation Solution
An automatic identification method and apparatus that uses image processing techniques to analyze immunoreagent card results, including binarization, histogram analysis, and brightness equalization to accurately distinguish positive and negative results, enhancing accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual eye observation is used to confirm detection results, then the method is simple and requires minimal equipment, but the accuracy of reading weak positives is low and misjudgment is likely to occur
Solution Approach 1:
The patent replaces the manual mechanical observation system with an automated image processing system. A photographing device captures images of the immunoreagent card, and computer software automatically analyzes the detection lines through image processing algorithms, substituting human visual judgment with automated digital analysis to improve accuracy of weak positive detection
Solution Approach 2:
The patent introduces an intermediary image processing system between the immunoreagent card and the final result interpretation. The system uses photographing devices to capture images and employs software algorithms as intermediaries to analyze and interpret the detection lines, providing an objective measurement that eliminates subjective human error
2Productivity
If staff manually recover and confirm reagent cards, then the process is straightforward, but the workload and consumption of manpower and material resources are very large
Solution Approach 1:
The patent enables the immunoreagent card system to perform self-reading of results. Users can photograph the detection card themselves using mobile devices, and the automated image processing software independently analyzes the results without requiring staff intervention for each card, allowing the system to serve itself in the result reading process
Solution Approach 2:
The patent replaces the manual mechanical process of staff reviewing and confirming each reagent card with an automated digital image analysis system. The system uses computer vision and image processing algorithms to automatically interpret detection lines, substituting human labor with automated technological processes to reduce workload
3Reliability
If centralized immunodetection is implemented, then comprehensive detection can be achieved, but it requires mobilizing a lot of manpower and material resources and creates risk of mutual infection
Solution Approach 1:
The patent segments the centralized detection process into individual decentralized units. Each person performs their own detection using personal immunoreagent cards, dividing the collective detection task into independent individual tests. This segmentation eliminates the need for centralized processing while maintaining comprehensive detection coverage across the population
Solution Approach 2:
The patent enables individuals to perform their own detection independently without requiring centralized processing facilities. Each person uses their own reagent card and can photograph and analyze results independently, allowing the detection system to serve itself at the individual level rather than requiring centralized resource mobilization
Data Source
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AI summary
The present invention provides an automatic identification method, apparatus and device for detection results of an immunoreagent card. The method includes: identifying a detection character and an identification code on a detection image of an obtained immunoreagent card; forming a corresponding target area based on the detection character, determining a central sub-area in the target area and calculating histogram information of the central sub-area; detecting a non-uniform area in the target area when the histogram information of the central sub-area is between a minimum grayscale statistical threshold and a maximum grayscale statistical threshold, and conducting brightness equalization processing on the non-uniform area; calculating the histogram information of the target area after equalization processing and determining a chromaticity of the target area based on a grayscale statistical threshold; forming an immune result of automatic identification of the immunoreagent card according to the chromaticity of the target area corresponding to each detection character; and binding the identified immune result with a serial number corresponding to the identification code of the immunoreagent card, and returning the identified immune result to a user.