Bacterial Colony Classification Device with Operator Feedback Loop
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Solution Overview
Problem
Current automated systems for classifying bacterial colonies on petri dishes struggle to accurately replicate the results of laboratory technicians, often requiring manual intervention and additional cultivation steps to achieve the correct bacterial concentration, leading to inefficiencies and increased time in processing large samples.
Innovation Solution
A device with an input unit for specifying classification numbers, an MD calculation processing unit for adjusting feature quantities, and a history storage unit to store classification conditions and results, allowing for the automatic adjustment of bacterial colony numbers and classification accuracy, enabling efficient operation without manual reselection or additional cultivation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated recognition and collection of bacterial colonies is performed, then productivity is improved, but measurement precision deteriorates due to inability to accurately replicate technician classification
Solution Approach 1:
The system displays classified bacterial colony images to the operator, who provides feedback by selecting correct classifications and indicating incorrect ones. This feedback loop allows the machine learning model to iteratively improve its classification accuracy by adjusting its decision boundaries based on actual technician judgments, thereby resolving the contradiction between automated processing speed and classification precision.
Solution Approach 2:
The system enables self-service classification where the machine learning model autonomously performs bacterial colony classification without requiring continuous manual intervention. The operator only needs to provide initial feedback on a few samples, after which the system automatically learns and applies classification rules, achieving both high productivity and improving precision over time.
2Measurement precision
If manual selection of bacterial colonies is performed, then measurement precision is maintained, but productivity deteriorates due to time-consuming processes
Solution Approach 1:
The system creates a digital copy of the bacterial colony images and uses machine learning to automatically classify them, replacing the need for physical manual selection. The operator reviews the automated classification of digital copies and provides feedback, which then trains the system to improve its automatic classification capability, achieving high productivity while maintaining precision through iterative learning.
3Measurement precision
If additional cultivation steps are performed to achieve correct bacterial concentration, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary classification of bacterial colonies based on image features (color, shape, size) before the actual measurement process. By pre-sorting and identifying the correct bacterial colonies and their concentrations through machine learning, the system eliminates the need for subsequent cultivation steps to achieve the correct bacterial concentration, thereby reducing time loss while maintaining measurement precision.
Data Source
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AI summary
When automatically classified results are different from judgment of a laboratory technician, the laboratory technician has to reselect the bacterial colonies one-by-one to be a pickup colony through watching the displayed image. To get rid of the inconvenience, provided is a pretreatment device for a bacteria test comprising: a specification unit by which an operator instructs to specify the number of bacterial colonies and the increased/ decreased number of the bacterial colonies to be displayed; and a display unit for displaying classification results obtained following the operator's instruction. The pretreatment device for a bacteria test facilitates the automatically classified results to be brought close to the judgment of the laboratory technician, resulting in the saving of the time required for checking the appropriate bacterial colonies for the pickup colony.