Staining Threshold Resetting for Accurate Cell State Determination
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for determining the stained state of tissue specimens are prone to artifacts and require subjective human judgment, making it difficult to efficiently optimize thresholds for accurate analysis.
Innovation Solution
A method for optimizing thresholds in image cytometry that involves specifying cell regions, setting temporary thresholds, displaying determination results, and allowing user input to correct and reset thresholds based on judgment, reducing the burden on users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a threshold is manually determined by skilled person's judgment, then the determination accuracy is improved, but the time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary automatic threshold determination using image information before manual adjustment. This preliminary action provides a starting point that is already reasonably accurate, reducing the time needed for manual optimization while maintaining determination accuracy.
Solution Approach 2:
The system displays determination results to the user and receives feedback on incorrect determinations. Based on this feedback, the threshold is automatically adjusted and redetermined. This feedback loop enables the system to learn from user corrections and converge to an optimal threshold efficiently, combining automatic processing with human judgment.
2Productivity
If automatic threshold determination is performed without manual intervention, then the productivity is improved, but the measurement precision deteriorates due to artifacts and staining variations
Solution Approach 1:
The system presents automatic determination results to the user and receives feedback on errors. This feedback is used to iteratively adjust the threshold until correct determinations are achieved. This approach maintains high productivity by automating the process while ensuring precision through human-in-the-loop verification and correction.
Solution Approach 2:
The system automatically adjusts the threshold based on user feedback without requiring manual reconfiguration. After the user corrects determination errors, the system self-adjusts the threshold parameters and continues processing, reducing the need for continuous manual intervention while maintaining accuracy.
3Quantity of substance
If multiple immunostaining are performed sequentially on the same specimen, then the information quantity is improved, but the reliability deteriorates due to result mismatch possibilities
Solution Approach 1:
The system determines thresholds and evaluates stained states independently for each immunostaining channel based on its specific image characteristics. This local optimization ensures that each staining result is accurately determined according to its own distribution properties, preventing cross-contamination of threshold settings and ensuring result reliability across multiple stainings.
Data Source
AI summary
A threshold determination method includes a region specification step of specifying cell regions corresponding to individual cells in an image obtained by imaging the biological specimen, a determination step of setting temporarily a threshold for staining density quantitatively indicating the degree of staining of the cell region, comparing the staining density and the threshold for each of the cell regions and determining whether a stained state is positive or negative for staining, a receiving step of displaying a determination result of the stained state of each of the cell regions and receiving an operation input of a user to change the determination result for each cell region, and a resetting step of resetting the threshold in accordance with the determination result after change. It is possible to optimize effectively a threshold used in determining a stained state from an image of an immunohistostained specimen while human judgment is made.