Automated Robotic Microscopy for Precise Sample Re-imaging
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Solution Overview
Problem
Existing microscopy systems lack the capability for high-throughput and high-content analysis of biological samples, particularly in reducing user intervention and enabling precise re-imaging of the same field over time.
Innovation Solution
The development of automated robotic microscopy systems that include an imaging device, a transport device, a processor, and memory with instructions for acquiring images, identifying fiduciary marks, and aligning samples for precise re-imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated robotic microscopy systems are implemented, then productivity and throughput are improved, but device complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a robotic arm for sample transport, an imaging device for capturing images, a processor for image analysis, and a sample holder for positioning. This segmentation allows each component to be optimized independently while working together to achieve high throughput automated microscopy.
Solution Approach 2:
The robotic arm is configured to interact with multiple imaging devices and perform various operations including sample retrieval, positioning, and re-imaging. The system can analyze different biological materials using the same core infrastructure, making it a universal platform for high-content screening.
2Measurement precision
If automated sample positioning and alignment are implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The processor identifies fiduciary marks on the sample and uses this information to calculate the actual position of the sample. This feedback is used to generate alignment instructions for the robotic arm, enabling precise re-positioning of the sample to the same field of view despite variations in initial placement.
Solution Approach 2:
Manual mechanical alignment operations are replaced with an automated system that uses image processing to identify fiduciary marks and computational algorithms to determine positioning corrections. The robotic arm executes these corrections automatically, eliminating the need for manual intervention.
3Productivity
If automated image acquisition and analysis systems are implemented, then productivity is improved, but ease of operation deteriorates
Solution Approach 1:
The system performs self-alignment by automatically identifying fiduciary marks on the sample and calculating the necessary positioning corrections. The processor generates and executes alignment instructions without user intervention, and the robotic arm autonomously re-positions samples for re-imaging, making the system self-sufficient.
Solution Approach 2:
Fiduciary marks are pre-positioned on the sample during sample preparation. These marks serve as reference points that enable the automated system to quickly locate and align with the sample area of interest without requiring manual searching or adjustment during the imaging process.
Data Source
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AI summary
The present disclosure provides automated robotic microscopy systems that facilitate high throughput and high content analysis of biological samples, such as living cells and/or tissues. In certain aspects, the systems are configured to reduce user intervention relative to existing technologies, and allow for precise return to and re-imaging of the same field (e.g., the same cell) that has been previously imaged. This capability enables experiments and testing of hypotheses that deal with causality over time with greater precision and throughput than conventional microscopy methods.