Medical Image Processor for Quantitative HER2 Protein Analysis
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Solution Overview
Problem
Current methods for detecting HER2 protein overexpression in tissue samples, such as the DAB staining method, lack quantitative capabilities and are dependent on manual analysis, making them inaccurate and labor-intensive.
Innovation Solution
A medical image processor that analyzes cell shape and fluorescent images to quantify HER2 protein expression by extracting cell nuclei and fluorescent bright points, calculating feature amounts, and generating synthesis images for annotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the DAB staining method is used to detect HER2 protein, then the detection process is simplified, but quantitative capability is lost and accuracy decreases
Solution Approach 1:
The patent introduces fluorescent bright point extraction as an intermediary step between the simple DAB staining process and quantitative analysis. By detecting fluorescent signals from HER2-specific antibodies conjugated with fluorescent markers, the system bridges the gap between ease of operation and measurement precision, enabling automated quantitative assessment without complex manual procedures
Solution Approach 2:
The patent replaces manual visual assessment and subjective interpretation with automated image processing algorithms. The system uses computer-based analysis to extract cell nuclei, identify fluorescent bright points, and calculate HER2 expression levels, substituting human judgment with objective computational methods that provide both simplicity and quantitative accuracy
2Adaptability or versatility
If manual analysis is used to assess HER2 expression, then flexibility is maintained, but labor intensity increases and accuracy decreases
Solution Approach 1:
The patent implements self-service through automated image processing where the system performs all analysis steps autonomously. The computer automatically extracts cell nuclei, identifies fluorescent bright points, calculates HER2 expression levels, and generates diagnostic results without requiring manual intervention, thereby eliminating labor intensity while maintaining analytical flexibility through programmable parameters
Solution Approach 2:
The patent segments the complex analysis process into distinct automated modules: cell nucleus extraction, fluorescent bright point detection, and HER2 expression calculation. This segmentation allows each function to be independently optimized and automatically executed, improving productivity while maintaining the flexibility to adjust individual modules as needed
3Measurement precision
If the FISH method is used to examine HER2 gene, then accuracy is improved, but process complexity and cost increase
Solution Approach 1:
The patent extracts only the essential quantitative measurement function from the complex FISH methodology. By using fluorescent immunohistochemistry with automated image analysis, the system isolates the critical aspect of FISH (fluorescent signal quantification) while eliminating unnecessary complexity such as probe hybridization and complex interpretation protocols, thereby maintaining accuracy with reduced process complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and quantitative assessment of HER2 protein expression, reducing reliance on manual analysis and improving diagnostic precision for prognostic purposes.
Implementation Method 1
a fluorescent image showing expression of a specific protein in the tissue slice as a fluorescent bright point
Data Source
AI summary
A medical image processor and storage medium are shown. According to one implementation, a medical image processor includes an input unit, an operation unit, a cell nucleus extracting unit, a fluorescent bright point extracting unit, a feature amount calculating unit, and an output unit. The input unit is used to input a cell shape image showing a shape of a cell and a fluorescent image showing expression of a specific protein as a fluorescent bright point. The operation unit is used to specify an analysis target region. The cell nucleus extracting unit extracts a region of a cell nucleus. The fluorescent bright point extracting unit extracts a fluorescent bright point. The feature amount calculating unit calculates a feature amount showing an expression amount of the specific protein. The output unit outputs the calculated feature amount.