Cell State Determination Using Time-Series Image Analysis
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Solution Overview
Problem
Existing cell culture evaluation methods struggle to accurately determine the degree of cell growth from images, especially when images with different growth stages have similar textures, leading to insufficient accuracy in determining cell states.
Innovation Solution
A culturing assistance device and method that utilize a processor to acquire time-series images of cell cultures, calculate state probabilities, and apply state change rule information to determine cell growth stages based on the change history, rather than relying solely on still image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If still image analysis is used to determine cell growth state, then the analysis process is simple and fast, but the determination accuracy is insufficient when images with different growth stages have similar textures
Solution Approach 1:
The patent transitions from two-dimensional still image analysis to four-dimensional analysis by incorporating time-series data (adding the time dimension). Multiple images captured at different time points are analyzed together with state change rules to determine cell growth states, resolving the accuracy limitation of single-image analysis while maintaining manageable complexity through systematic processing.
Solution Approach 2:
The system performs preliminary classification of cell states (e.g., young, mature, degraded) and establishes state change rules in advance. By pre-defining the classification framework and transition rules, the system prepares the analytical structure before actual measurement, enabling more accurate determination without excessive complexity during the measurement phase.
2Measurement precision
If time-series image analysis with state change rules is applied, then cell state determination accuracy is improved, but the analysis complexity and processing time increase
Solution Approach 1:
The system applies partial action by focusing analysis on key state transition points and critical changes in the time-series data rather than processing every frame uniformly. By identifying and analyzing only the significant state changes that matter for determination accuracy, the system reduces unnecessary processing time while maintaining high accuracy for critical measurements.
Solution Approach 2:
The system uses feedback mechanisms where the determined cell state at each time point informs the analysis of subsequent time points through state change rules. This feedback loop allows the system to leverage previous determination results to guide future analysis, reducing redundant processing and optimizing the overall analysis time while maintaining cumulative accuracy improvements.
Data Source
AI summary
There is provided a culturing assistance device including: a memory which stores a program; and a processor which executes the program, wherein the processor executes the program to implement: acquiring a plurality of captured images in which cells are captured in time series; calculating a probability that a state of the cells shown in the acquired image is a certain state; reading predetermined state change rule information which is stored in a storage unit and indicates a relationship among a plurality of states of the cells in the time-series; and determining the state of the cell based on the calculated probability and the read state change rule information.