Cell Quality Evaluation Using Adaptive Re-Imaging Regions
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Solution Overview
Problem
Existing methods for evaluating cell quality in large-volume cell-culture containers are inaccurate due to the difficulty in imaging the entire container, and using large, costly microscopes is impractical for ordinary users.
Innovation Solution
A cell quality evaluation apparatus and method that uses a processor to estimate cell quality from multiple images, derive estimation errors, and perform re-imaging in specific regions to ensure accuracy, even in large containers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire cell-culture container is imaged to reduce estimation error, then measurement precision improves, but device complexity and cost increase due to requiring large microscopes
Solution Approach 1:
The cell-culture container is divided into multiple imaging regions that are imaged separately. Instead of requiring a single large microscope to capture the entire container, the system segments the imaging task into multiple smaller regions that can be captured by a standard microscope, then combines the results to achieve accurate quality estimation for the entire container.
Solution Approach 2:
The system images only a selected plurality of imaging regions from the entire cell-culture container rather than the whole container. By strategically selecting regions and using estimation algorithms, the system achieves accurate quality assessment without the excessive action of imaging every region, reducing the required microscope capability while maintaining precision.
2Measurement precision
If the number of imaging regions is increased to reduce estimation error, then measurement precision improves, but loss of time increases due to more imaging operations
Solution Approach 1:
The system determines an optimal number of imaging regions that provides sufficient accuracy without requiring complete coverage. By selecting a representative subset of regions rather than imaging the entire container, the system achieves acceptable measurement precision while significantly reducing the time required for imaging operations.
Solution Approach 2:
The quality estimation result and estimation error are calculated from the imaged regions, and this feedback is used to determine whether additional imaging is needed. The system can adaptively decide when sufficient accuracy has been achieved, avoiding unnecessary additional imaging time while ensuring the measurement precision meets required thresholds.
3Measurement precision
If the area of imaging regions is increased to reduce estimation error, then measurement precision improves, but the number of regions that can be imaged decreases
Solution Approach 1:
The system segments the cell-culture container into multiple smaller imaging regions rather than using a few large regions. This segmentation allows a greater number of regions to be imaged, providing more data points for quality estimation and reducing estimation error through statistical averaging across multiple independent measurements.
Data Source
AI summary
A cell quality evaluation apparatus performs a process including estimation processing of estimating a quality of cells in the entirety of a cell-culture container by determining feature quantities from a plurality of images and calculating an average value of the feature quantities; derivation processing of deriving an estimation error of the quality estimated in the estimation processing, based on a variation of the feature quantities in the plurality of images and imaging information related to an area of a plurality of imaging regions; and imaging control processing of causing a imaging apparatus to perform re-imaging on at least one re-imaging region different from the plurality of imaging regions in a case where the estimation error is out of an allowable range.