Bacteria Test Imaging with Luminance Statistics for Uneven Growth
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Solution Overview
Problem
Existing methods for determining bacterial growth and inhibition based on microscopic images face challenges due to varying threshold settings for binarization, leading to inaccurate determinations, especially when growth occurs unevenly across the image.
Innovation Solution
A bacteria test apparatus and method that utilize statistical features such as mean, median, and mode of luminance values from captured images, combined with a minimum filter to enhance edge detection, allowing for accurate and quick determination of bacterial growth and inhibition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If automatic binarization is performed using discriminant analysis to adapt to varying bacterial growth degrees, then the method can handle different growth stages, but the threshold setting becomes improper when growth occurs over the entire image, leading to inaccurate detection
Solution Approach 1:
The patent divides the image into multiple regions (e.g., quadrants or zones) and performs binarization and feature extraction independently in each region. This segmentation allows the system to handle uneven bacterial growth patterns without being skewed by overall image characteristics, enabling accurate detection even when growth occurs throughout the entire image.
Solution Approach 2:
The patent applies different processing thresholds and parameters to different regions of the image based on local bacterial growth characteristics. By adjusting binarization thresholds and feature extraction parameters according to the specific growth pattern in each region, the system maintains high measurement precision while adapting to varying growth degrees across the image.
2Loss of time
If traditional microscopic image analysis is used to quickly obtain antibacterial susceptibility results, then the testing time is reduced, but the accuracy of growth state determination deteriorates due to improper binarization threshold setting
Solution Approach 1:
The patent segments the image analysis process into multiple independent regional analyses, allowing parallel processing that maintains speed while improving accuracy. Each region can be processed simultaneously, reducing total testing time while the segmented approach prevents threshold setting errors that would occur in single-image analysis.
Solution Approach 2:
The patent performs preliminary image segmentation and regional characteristic analysis before final growth determination. This preliminary action prepares the data structure and identifies key features in advance, enabling rapid accurate determination without requiring time-consuming iterative threshold adjustment.
3Adaptability or versatility
If binarization threshold is adjusted to accommodate varying bacterial growth degrees, then the method becomes more flexible, but detection errors increase when growth is uniform across the entire image
Solution Approach 1:
The patent segments the image into multiple regions and performs binarization independently in each region. This segmentation allows the system to maintain flexible adaptation to different growth patterns while preventing detection errors by localizing the binarization process to specific regions rather than applying a single global threshold.
Solution Approach 2:
The patent incorporates feedback mechanisms that continuously monitor the binarization results and adjust thresholds based on the actual bacterial growth patterns detected in each region. This feedback loop ensures high reliability by automatically optimizing threshold settings according to the specific growth conditions, preventing errors while maintaining flexibility.
Data Source
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AI summary
Provided is a technique that enables accurate determination as to whether growth of bacteria has occurred or been inhibited. A bacteria test apparatus according to the present disclosure includes a microscope optical system which captures images of bacteria in each of a plurality of wells at a plurality of time points, the plurality of wells each holding a culture solution containing an antibacterial drug and the bacteria, an arithmetic unit which calculates a feature of luminance value for each of the images of the bacteria, a determination unit which determines whether growth of the bacteria has occurred in the wells based on a change in the feature of luminance value, and a display device which displays a determination result output from the determination unit. The arithmetic unit calculates, as the feature of luminance value, a feature including at least one of a mean, a median, or a mode (see FIG. 4).