Microorganism Growth Detection via Image Realignment
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Solution Overview
Problem
Current methods for detecting microorganism growth in Petri dishes are unreliable due to factors like scratches, condensation, and unintentional movements between image acquisitions, which can lead to erroneous interpretations of microorganism colonies.
Innovation Solution
A method involving primary and secondary realignment of images acquired at different times, using a lateral label for initial alignment and subimage meshing for fine alignment, along with correlation and contrast parameter evaluation to accurately detect and evaluate potential microorganism growth zones, minimizing the impact of artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image comparison is performed to detect microorganism colonies, then microorganism growth can be detected, but false detections occur due to scratches, condensation, and structural defects appearing as distinct elements
Solution Approach 1:
The patent applies preliminary realignment of images before comparison by detecting reference elements (scratches, condensation, structural defects) and calculating transformation parameters to compensate for their positions. This preliminary action removes the harmful effect of these artifacts before the actual microorganism detection comparison is performed, allowing reliable detection while eliminating false positives from artifacts.
2Ease of operation
If images are compared without realignment, then processing is simple, but movements between acquisitions cause shifts that prevent accurate comparison
Solution Approach 1:
The patent performs preliminary realignment of images by detecting reference elements and calculating transformation parameters (translation, rotation, scaling) before comparison. This automated preliminary action maintains ease of operation while achieving precise alignment, as the system automatically compensates for movements between image acquisitions without requiring manual intervention.
Solution Approach 2:
The patent uses reference elements (scratches, condensation, structural defects) as intermediaries to establish correspondence between images. These elements serve as mediators that enable the calculation of transformation parameters, allowing accurate realignment while maintaining automated processing. The reference elements bridge the gap between images taken at different times and positions.
3Measurement precision
If reference elements are used for realignment, then alignment accuracy improves, but the system becomes more complex
Solution Approach 1:
The patent applies self-service by automatically detecting reference elements and calculating transformation parameters without user intervention. The system uses itself to perform the realignment operation by identifying features in the images and computing the necessary transformations, thereby improving precision while avoiding the complexity of manual realignment procedures.
Data Source
AI summary
Method for determining microorganism growth in a biological sample likely to contain microorganisms, said biological sample being contained in an analysis container, said analysis container being subjected to an incubation of a determined duration, said method comprising:acquiring a first plurality of initial images of the analysis container at a first acquisition time T1, before or during the incubation;acquiring a second plurality of final images of the analysis container at a second acquisition time T2, during or after the incubation;realigning each initial image of the first plurality of initial images acquired, with each corresponding final image of the second plurality of final images acquired;locating at least one potential microorganism growth zone in at least one image of the second plurality of images acquired;evaluating the content of the potential microorganism growth zone identified in order to determine the presence of microorganisms.