Automated Myoblast Nuclei Counting for Consistent Cell Sheet Quality
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Solution Overview
Problem
The quality of sheet-shaped cell cultures, particularly in determining the multinucleated state of myoblast cells, varies significantly due to reliance on visual determination by operators, leading to inconsistencies and inefficiencies in producing high-quality cultures for tissue repair.
Innovation Solution
A system that measures the shape of myoblast cells and calculates the number of nuclei based on specific parameters, using an imaging unit and analysis software to systematically determine the multinucleated state, potentially omitting the need for cell staining and observation, and includes a learning unit to update parameters for improved accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual determination of stained cells by operator is used, then the multinucleated state can be determined, but the determination result varies among operators causing variation in quality
Solution Approach 1:
The patent replaces the manual visual determination method with an automated image processing system. The system captures images of cells, automatically segments nuclei using image processing algorithms, counts nuclei per cell, and determines multinucleated states without human intervention, thereby eliminating operator variability and ensuring consistent, reliable results.
Solution Approach 2:
The system enables self-service by allowing the cell culture quality determination to be performed automatically by the imaging and analysis system itself. The system independently completes the entire workflow from image capture to multinucleated state determination without requiring operator involvement, making the process self-sufficient and reproducible.
2Measurement precision
If visual determination method is used, then multinucleated state can be assessed, but the process is time-consuming and inefficient
Solution Approach 1:
The patent replaces the time-consuming manual visual inspection with an automated digital imaging and image processing system. The system rapidly captures cell images, processes them through automated segmentation and nucleus counting algorithms, and generates determination results much faster than manual methods, significantly improving productivity while maintaining determination accuracy.
Solution Approach 2:
The system performs preliminary action by automatically capturing and processing cell images before final quality assessment is needed. The image processing and nucleus counting are completed in advance, allowing rapid determination of multinucleated states without requiring time-consuming manual examination when results are needed.
3Measurement precision
If staining and visual observation are performed, then multinucleated cells can be identified, but additional steps and complexity are introduced
Solution Approach 1:
The patent extracts the essential function of nuclei identification from the complex staining and visual observation process. By using image processing algorithms to detect and segment nuclei based on image intensity and morphological features, the system eliminates the need for staining steps while maintaining the ability to accurately identify and count nuclei, thereby simplifying the overall process.
Solution Approach 2:
The system substitutes the complex manual staining and visual observation workflow with an automated digital imaging and computational analysis system. The image processing algorithm automatically performs nucleus detection, segmentation, and counting without requiring staining reagents or manual microscopy, reducing process complexity while preserving identification accuracy.
Data Source
AI summary
A stable and efficient system that determines a multinucleated state of myoblast cells, the system including a storage unit that stores a cell culture substrate containing the myoblast cells, a measurement unit that measures a shape of the myoblast cells, and an analysis unit that calculates the number of nuclei in the individual myoblast cells based on a parameter.