Automated Virus Imaging System with Cloud Analysis
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Solution Overview
Problem
Conventional transmission electron microscopes (TEMs) are structurally complex and expensive, with virus imaging and analysis being manual, tedious, slow, and labor-intensive, lacking in cost-effectiveness and reliability.
Innovation Solution
A rapid and automatic virus imaging and analysis system comprising electron optical sub-systems with large field of view and instant magnification switching, sample management sub-systems for automated loading and unloading of samples, virus detection and classification sub-systems for automated detection, and a cloud-based collaboration sub-system for image analysis and data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional transmission electron microscopes are used for virus imaging, then high resolution can be achieved, but the system becomes structurally complex and expensive
Solution Approach 1:
The system is divided into four independent subsystems (electron optical subsystem, sample management subsystem, virus detection and classification subsystem, and cloud-based collaboration subsystem), each performing a specific function. This segmentation allows the complex virus imaging task to be distributed across modular components, reducing overall system complexity while maintaining high resolution capabilities through the electron optical subsystem.
Solution Approach 2:
The electron optical subsystem is designed to handle multiple functions including imaging, magnification switching, and sample scanning within a single integrated unit. The sample management subsystem automatically performs loading, unloading, and positioning of multiple samples, providing universal sample handling capabilities that reduce the need for separate manual operations and equipment.
2Measurement precision
If manual virus imaging and analysis is performed, then detailed examination can be conducted, but the process becomes tedious, slow, and labor-intensive
Solution Approach 1:
The virus detection and classification subsystem automatically performs virus identification and classification based on images acquired by the electron optical subsystem. The sample management subsystem automatically loads and unloads samples without human intervention. These self-service capabilities eliminate manual, tedious operations while maintaining accurate virus analysis through automated detection algorithms.
Solution Approach 2:
The system incorporates automated feedback loops where images are continuously acquired, analyzed by the virus detection subsystem, and used to guide further imaging or classification decisions. The cloud-based collaboration subsystem provides feedback by storing and analyzing data from multiple sources, enabling continuous improvement of detection accuracy while maintaining high throughput through automated processing.
3Reliability
If conventional manual methods are used, then thorough analysis can be performed, but cost-effectiveness and reliability are reduced
Solution Approach 1:
The system replaces manual mechanical operations with automated electronic and software-based systems. The electron optical subsystem uses automated magnification switching and scanning, the sample management subsystem uses automated loading/unloading mechanisms, and the virus detection subsystem uses computational algorithms for classification. This substitution of mechanical/manual processes with automated systems improves reliability through consistent automated operations while reducing long-term costs through decreased labor requirements.
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
The system provides faster, more reliable, and cost-effective virus imaging and analysis, simplifying the structure and improving manufacturability, enabling rapid scanning and classification of virus samples with higher precision and efficiency.
Implementation Method 1
Although the system will be illustrated, explained, and exemplified by an electron optical sub-system such as a scanning transmission electron microscope (STEM)... it should be appreciated that the present invention can also be applied to other apparatuses of charged-particle beam such as a scanning electron microscope (SEM), transmission electron microscope (TEM)
Data Source
AI summary
A rapid and automatic virus imaging and analysis system includes (i) electron optical sub-systems (EOSs), each of which has a large field of view (FOV) and is capable of instant magnification switching for rapidly scanning a virus sample; (ii) sample management sub-systems (SMSs), each of which automatically loads virus samples into one of the EOSs for virus sample scanning and then unloads the virus samples from the EOS after the virus sample scanning is completed; (iii) virus detection and classification sub-systems (VDCSs), each of which automatically detects and classifies a virus based on images from the EOS virus sample scanning; and (iv) a cloud-based collaboration sub-system for analyzing the virus sample scanning images, storing images from the EOS virus sample scanning, and storing and analyzing machine data associated with the EOSs, the SMSs, and the VDCSs.