Microscope Autofocusing System Dynamic Rule Adaptation
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Solution Overview
Problem
Existing autofocusing systems for microscopes have static behavior, unable to adapt dynamically to sample conditions, and lack intelligent strategies to handle changes in focus positions over time, leading to inaccurate focus maps and potential experiment failure.
Innovation Solution
An autofocusing system that performs autofocusing procedures in cycles, using image content analysis to select the best focus based on image descriptors like contrast, information content, and entropy, and adapts parameters such as wavelength and spatial position based on dynamic rules and sample information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If classical autofocusing methods are used, then focus determination can be performed, but the system cannot adapt dynamically to changing sample conditions leading to inaccurate focus maps
Solution Approach 1:
The patent implements dynamic autofocusing by continuously monitoring image quality metrics (contrast, entropy, information content) and adjusting focus parameters in real-time based on detected changes in sample conditions. The system transitions from static focus determination to an adaptive process that responds to temporal variations in sample properties, ensuring accurate focus maps even when samples move or change morphology.
Solution Approach 2:
The system employs feedback mechanisms by evaluating image quality descriptors and using this information to adjust subsequent focusing operations. The focus determination process incorporates feedback loops where measured image metrics inform parameter adjustments, enabling the system to learn from and adapt to sample behavior patterns, thereby improving focus map accuracy under varying conditions.
2Measurement precision
If multiple images are collected for focus determination, then focus accuracy can be improved, but processing time increases
Solution Approach 1:
The patent applies partial action by collecting and evaluating only the necessary number of images required for adequate focus determination rather than exhaustive image sets. The system dynamically adjusts the number of images acquired based on convergence criteria and image quality metrics, stopping the acquisition process when sufficient focus information is obtained, thus reducing processing time while maintaining accuracy.
Solution Approach 2:
The system performs preliminary focus estimation using a subset of images or preliminary image quality assessments before committing to full focus determination procedures. This preliminary action allows the system to quickly identify obvious focus states or detect when extensive image collection is unnecessary, thereby reducing overall processing time while preserving measurement precision when needed.
3Reliability
If autofocusing is performed at every spatial position, then focus accuracy is maintained, but sample damage increases
Solution Approach 1:
The patent implements local quality by applying different autofocusing strategies to different spatial regions based on local sample characteristics and risk assessments. The system identifies regions where intensive autofocusing is necessary versus regions where it can be reduced or omitted, allowing focus accuracy to be maintained in critical areas while minimizing cumulative light exposure and sample damage in less critical regions.
Solution Approach 2:
The system performs autofocusing at only the necessary spatial positions rather than uniformly across the entire sample field. By using predictive models and focus map interpolation, the system determines that full autofocusing at every position is excessive, and instead performs focused measurements only where required, thereby maintaining adequate focus accuracy while reducing overall sample exposure to damaging light doses.
4Speed
If position detection methods are used, then autofocusing speed is improved, but precision decreases when no reference surface is present
Solution Approach 1:
The patent creates a universal autofocusing system that can operate effectively with or without reference surfaces by combining multiple detection approaches. The system automatically selects or switches between position detection methods (when reference surfaces are available) and image content analysis methods (when reference surfaces are absent), ensuring both speed and precision are maintained across diverse experimental conditions without requiring specialized equipment for each scenario.
Data Source
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AI summary
An autofocusing system (150) for a microscope (110) is proposed according to the invention. The autofocusing system (110) is adapted to perform an autofocusing procedure (200), the autofocusing procedure (200) comprising predefining a set of target points (201) for autofocusing, wherein at least one static or dynamic rule (211-217) is associated to each of the predefined target points (201) or to a subset thereof, the at least one rule (211-217) defining at least one initial setting and at least one adaptation instruction for at least one parameter influencing how an autofocusing operation is performed for the target point (201), initiating for each of the predefined set of target points (201) or a subset thereof an initial autofocusing operation (4) comprising the at least one initial setting as defined by the at least one rule (211-217) associated to the target point (201), initiating for each of the predefined set of target points (201) or a subset thereof an adapted autofocusing operation (4) based on the at least one adaptation instruction as defined by the at least one rule (211-217) associated to the target point (201), and further processing (7) an autofocus value for at least some of the target points (201), the autofocus value being obtained by the initial autofocusing operation (4) or by the adapted autofocusing operation (4). An autofocusing method for use in an autofocusing system (150) for a microscope (110) and a corresponding computer program is also part of the invention.