Microscope Sample Carrier Orientation Detection for 180° Rotation
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Solution Overview
Problem
Modern microscopes face challenges in accurately determining the orientation of sample carriers, particularly when they are rotated by 180 degrees, leading to incorrect designations and flawed measurements in long-term experiments due to software misinterpretation of sample receptacle orientations.
Innovation Solution
A microscopy system and method that utilize image analysis and machine-learned models to discriminate between orientations of sample carriers rotated by 180 degrees by analyzing predetermined structures and calculating an orientation indication, allowing for correct assignment of sample region identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual orientation check is performed, then orientation accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent replaces manual visual inspection and mechanical orientation checking with an automated image processing system. The microscopy system captures overview images and uses algorithmic analysis to automatically determine sample carrier orientation, substituting human operators with computational methods that provide both high accuracy and efficiency.
Solution Approach 2:
The system performs self-verification of orientation through automated image analysis. The microscopy system independently determines its own orientation state by processing overview images and comparing detected features against expected patterns, eliminating the need for external manual checking.
2Productivity
If automated software designation is used without orientation verification, then productivity is improved, but reliability deteriorates due to potential misidentification
Solution Approach 1:
The system implements a feedback mechanism where the automated orientation determination results are used to verify and correct software designations. The image processing analysis provides feedback on the actual orientation state, which then adjusts the sample receptacle identification to ensure accuracy while maintaining automated workflow efficiency.
Solution Approach 2:
The system performs preliminary orientation verification through image analysis before final sample receptacle designation is assigned. By determining orientation in advance and using it to guide the designation process, the system ensures reliable identification while maintaining automated productivity.
3Extent of automation
If overview image analysis is used for orientation determination, then automation extent is improved, but measurement precision may worsen due to image quality limitations
Solution Approach 1:
The system transitions from analyzing two-dimensional image data to determining three-dimensional orientation information. By processing overview images and extracting spatial relationships between features, the system derives accurate orientation angles and rotational states, converting planar image data into precise spatial orientation measurements.
Solution Approach 2:
The system combines multiple image processing techniques and analysis methods to achieve high precision orientation determination. By integrating feature detection, pattern recognition, and geometric analysis in a composite approach, the system overcomes limitations of individual methods and achieves both high automation and high precision.
Data Source
AI summary
In a computer-implemented method for determining an orientation of a sample carrier of a microscope, an overview image showing at least a part of a sample carrier with a plurality of sample regions is received. The overview image is evaluated in order to localize predetermined structures. At least one image region that shows at least one predetermined structure is analyzed in order to calculate an orientation indication that discriminates between orientations of the sample carrier that are rotated by 180° relative to each other.