Laser Microdissection Cut Verification via Image Sharpness
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Solution Overview
Problem
Laser microdissection systems face challenges in ensuring the reliability and accuracy of automatic or semi-automatic dissection processes, as incomplete cuts can occur, leading to dissectates being partially attached to the object or not collected correctly.
Innovation Solution
A method is introduced that involves acquiring image data of the dissection region using multiple focal planes to assess the completeness of the cut, analyzing for sharp structures, and adjusting the cutting process accordingly, with a control unit and computer program to automate the analysis and potential re-cutting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic or semi-automatic dissection process is used, then productivity is improved, but reliability deteriorates due to incomplete cuts
Solution Approach 1:
The system captures images of the dissectate after cutting and automatically analyzes them to detect incomplete cuts. The analysis unit processes the images to identify whether the dissectate is complete and properly detached, providing feedback that triggers automatic re-cutting if necessary. This closed-loop feedback mechanism ensures high reliability while maintaining automatic operation speed.
Solution Approach 2:
The system performs preliminary image capture and analysis immediately after the initial dissection process to identify any incomplete cuts before finalizing the procedure. By detecting and addressing incomplete cuts in this preliminary check phase, the system ensures complete dissection without requiring manual inspection, thus maintaining both productivity and reliability.
2Measurement precision
If manual inspection of dissectate is performed, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The system replaces manual visual inspection with an automated image analysis unit that processes captured images of the dissectate. The analysis unit uses automated image processing algorithms to detect incomplete cuts and assess dissectate completeness, eliminating the need for time-consuming manual inspection while maintaining or improving detection precision.
Solution Approach 2:
The system creates digital copies of the dissectate through image capture and uses these copies for automated analysis. By analyzing the image copy rather than requiring direct manual inspection of the physical dissectate, the system achieves rapid, precise evaluation without time loss, as the image analysis can be performed automatically and simultaneously with other process steps.
3Manufacturing precision
If multiple focal planes are used for image capture, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The system captures images at multiple focal planes (different depth levels) to obtain comprehensive views of the dissectate structure. By acquiring images at multiple z-depths and combining them through image fusion, the system achieves accurate three-dimensional reconstruction and precise boundary detection of the dissectate, ensuring complete cut verification while using standard microscopy capabilities.
Solution Approach 2:
The system merges multiple images captured at different focal planes into a single composite image or uses them collectively for analysis. This merging process integrates information from multiple depth levels to improve the accuracy of dissectate boundary detection and completeness assessment, achieving high manufacturing precision without requiring fundamentally new device components.
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 enhances the reliability of the dissection process by ensuring complete detachment and accurate collection of dissectates, reducing the occurrence of incomplete cuts and improving the overall precision of the laser microdissection system.
Implementation Method 1
carrying out the dissection process for cutting out a dissectate from an object in a first region of the object by a laser beam
Implementation Method 2
acquiring first image data of at least the first region of the object after the dissection process with a focal plane which is offset from an object plane along an optical axis
Data Source
AI summary
A method for checking a dissection process in a laser microdissection system includes carrying out the dissection process for cutting out a dissectate from an object in a first region of the object by a laser beam. First image data is acquired of at least the first region of the object after the dissection process. It is examined whether the first image data has sharp structures within a region to be separated by the dissection process in order to determine whether the dissection process was successful.