Microbial Agent Detection via Darker Region Segmentation
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Solution Overview
Problem
Current electron microscopy systems face challenges in accurately and rapidly detecting coronavirus particles in biological samples, often misidentifying subcellular structures as virions, and lack the ability to differentiate them from other microbial agents and organelles.
Innovation Solution
A system utilizing a scanning electron microscope and processing units to identify and crop darker regions in electron micrographs, which are more densely populated with microorganisms, and employ algorithms for precise identification of coronavirus particles, including shape and size criteria, to differentiate them from subcellular structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional electron microscopy is used to visualize Coronavirus particles, then detection capability is provided, but subcellular structures are misidentified as virions leading to false positives
Solution Approach 1:
The image analysis process is segmented into multiple stages: initial full-field scanning to identify darker regions, cropping of these regions, and then particle identification within the cropped areas. This segmentation allows the system to focus computational resources on relevant areas while maintaining high detection accuracy and reducing false positives from subcellular structures.
Solution Approach 2:
The system applies different processing qualities to different regions of the image. Full-field images are processed at lower resolution for rapid scanning, while darker regions are cropped and processed at higher resolution for accurate particle identification. This local quality approach improves both detection speed and precision without requiring high-resolution processing of the entire image.
2Measurement precision
If comprehensive image analysis is performed to accurately identify Coronavirus particles, then detection precision is improved, but processing time increases
Solution Approach 1:
The image analysis is divided into sequential stages: rapid full-field scanning to locate darker regions, followed by cropping and detailed analysis only of those regions. This segmentation enables the system to achieve high particle identification accuracy while minimizing processing time by avoiding comprehensive analysis of the entire image.
Solution Approach 2:
The system performs partial analysis by focusing computational resources only on darker regions that are likely to contain particles, rather than analyzing the entire image. This partial action approach maintains high detection precision while significantly reducing processing time compared to comprehensive image analysis.
3Measurement precision
If high-resolution imaging is used to differentiate Coronavirus virions from other structures, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The imaging and analysis process is segmented into full-field scanning at lower resolution followed by cropped high-resolution analysis of darker regions only. This segmentation enables the system to maintain high differentiation capability while improving productivity by avoiding high-resolution imaging of the entire sample area.
Solution Approach 2:
The system applies high-resolution imaging only to darker regions that are likely to contain particles, rather than processing the entire image at high resolution. This partial action approach maintains measurement precision for particle differentiation while significantly improving productivity by reducing the total area requiring high-resolution processing.
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 approach enables rapid and accurate detection of coronavirus particles, improving diagnostic reliability and reducing false positives, with the capability to process samples within minutes and detect new pathogens without the need for new reagents.
Implementation Method 1
electron microscopy (EM)... investigators have inaccurately reported subcellular structures... as Coronavirus virions in electron micrographs
Data Source
AI summary
A system for identifying microbial agents such as virus particles in a sample. The system includes at least one processing unit for identifying in an electron micrograph obtained from the sample a darker region and identifying virus particles within the darker region. The system can optionally include an electron microscope, a sample collector and sample treatment chamber.