Laser Microdissection Trajectory Prediction
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Solution Overview
Problem
Current laser microdissection methods face challenges in precisely collecting dissectates due to unpredictable dissectate trajectories, which limits the use of smaller multiwell plates with more wells, as the trajectories can deviate from the vertical direction, making it difficult to collect dissectates in the intended vessels.
Innovation Solution
A method using a learning mode to predict and adjust the positioning of dissectate collection vessels based on the analysis of dissectate trajectories, determined by repeatedly performing laser microdissection steps and applying machine learning algorithms to correlate the releasing laser pulses with the trajectories, allowing for precise alignment of receptacles with the predicted paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If smaller multiwell plates with more wells are used to increase productivity, then the quantity of dissectates that can be collected increases, but the reliability of collection decreases because dissectate trajectories are unpredictable and may deviate from vertical direction
Solution Approach 1:
The system performs preliminary tracking of dissectate trajectories during the cutting and release process, then uses this trajectory information to predict and adjust the positioning of collection vessels before the dissectates arrive, ensuring accurate collection in smaller multiwell plates
Solution Approach 2:
The system continuously monitors the actual trajectories of released dissectates and uses this feedback information to dynamically adjust the positioning of collection vessels, improving collection reliability while maintaining high productivity
2Manufacturing precision
If traditional fixed positioning of collection vessels is used, then the device complexity is low, but the manufacturing precision of collection decreases due to unpredictable dissectate trajectories
Solution Approach 1:
The system transitions from static fixed positioning to dynamic adaptive positioning, where the position of collection vessels is continuously adjusted based on real-time trajectory tracking and prediction, achieving high collection precision through motion control
Solution Approach 2:
The system replaces purely mechanical fixed positioning with an intelligent control system that uses optical tracking and computational algorithms to predict and adjust vessel positions, substituting mechanical simplicity with electronic-intelligent complexity
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 reliable and precise collection of dissectates in smaller multiwell plates by accurately positioning receptacles according to predicted trajectories, improving the reliability and efficiency of the dissectate collection process.
Implementation Method 1
dissectate regions of the sample are at least partially circumcised and released from the sample as the dissectates by applying laser pulses of a laser beam
Data Source
AI summary
A method for obtaining dissectates from a microscopic sample using a laser microdissection system having a laser unit includes: a) at least partially circumcising and releasing from the sample dissectate regions of the sample as the dissectates using laser pulses provided by the laser unit; b) transferring the dissectates, by being released from the sample, along dissectate trajectories into receptacles of a dissectate collection unit; and c) positioning the receptacles of a dissectate collection unit using a positioning unit to collect the dissectates. The positioning of the receptacles of the dissectate collection unit using the positioning unit is automatically performed based on estimates of the dissectate trajectories, the estimates of the dissectate trajectories being obtained in a learning mode, the learning mode including obtaining dissectates by repeatedly performing at least steps a) and b). Parameters of the dissectate trajectories are determined for a plurality of dissectates.