Automated Microbial Colony Imaging for Early Growth Detection
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Solution Overview
Problem
Current imaging technologies for detecting microbial growth on culture plates are difficult to automate due to their highly visual nature, making it challenging to identify and distinguish colonies, especially when they are of different sizes and shapes and are touching each other.
Innovation Solution
An automated method for evaluating microbial growth on plated media involves inoculating culture media with a biological sample, incubating it, and then using digital imaging to capture images at different times. The method includes aligning the images, comparing pixels to identify changes, determining threshold contrast, and correlating objects with biomass to determine if the sample is pure and if the biomass meets certain thresholds for further analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If colonies are allowed to grow longer to improve contrast and ease of identification, then identification accuracy improves, but colonies may touch each other and purity of target colony decreases
Solution Approach 1:
The system performs preliminary imaging and analysis at multiple time points during incubation to identify colonies at the optimal size before they touch adjacent colonies. By capturing images at predetermined time intervals and analyzing colony characteristics early, the system determines the best time to pick colonies while they are still isolated and pure.
Solution Approach 2:
The system uses feedback from sequential imaging to monitor colony growth in real-time. By comparing images taken at different time points, the system can detect when colonies reach the optimal size for picking and alert the user or automatically initiate the picking process before colonies begin to touch each other.
2Object-affected harmful factors
If imaging is performed earlier to prevent colony confluence, then colony purity is maintained, but contrast between colonies and background is poor
Solution Approach 1:
The system performs preliminary imaging at the start of incubation and continues to image at predetermined intervals. By having multiple time-point images available, the system can identify colonies when they first become visible and track their growth, allowing for early detection while maintaining the ability to wait for better contrast.
Solution Approach 2:
The system changes the parameter of time by capturing images at multiple predetermined time intervals during incubation. This allows the same sample to be evaluated at different stages of growth, enabling the system to select the optimal imaging time point for each colony based on its specific growth rate and characteristics.
3Measurement precision
If manual inspection methods are used to ensure accurate colony identification, then identification accuracy improves, but automation and productivity decrease
Solution Approach 1:
The system performs self-service by automatically capturing images, analyzing colony characteristics, and determining which colonies meet the selection criteria. The automated image analysis algorithms identify colonies based on size, shape, and contrast parameters, eliminating the need for manual inspection while maintaining high accuracy.
Solution Approach 2:
The system replaces manual mechanical inspection with automated digital imaging and computer-based image analysis. The optical system captures images and software algorithms automatically identify and characterize colonies, substituting human visual inspection with machine-based detection that is both accurate and high-throughput.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This automated method enables early detection of microbial growth, improves the speed and accuracy of colony identification, and facilitates the determination of whether a sample is pure and has sufficient biomass for further testing, thereby streamlining laboratory workflows and reducing costs.
Implementation Method 1
obtaining a first digital image of the inoculated media at a first time (t0)... obtaining a second digital image of the inoculated media at a second time (tx)
Implementation Method 2
a provided culture media is inoculated with a biological sample disposed in a container that is substantially optically transparent
Data Source
AI summary
An imaging method for earliest microbial growth detection. The method uses images to determined colony biomass, and the colony biomass determines when the colony can be picked for analysis for identification or antibiotic susceptibility testing. If the sample source is not a pure sample source additional incubation may be required to permit an increase in biomass of the colonies prior to pick.