Real-Time Estimator Adaptation for Microscope Localization
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Solution Overview
Problem
Current fluorescence microscopy methods, such as MINFLUX, face challenges in achieving real-time unbiased localization of emitters due to the need for post-processing to account for experimental conditions like spatial intensity distribution and signal-to-noise ratio, which slows down sample optimization and throughput.
Innovation Solution
A method and apparatus that adapt the estimator in real-time by determining a value representative of background noise from acquired photon counts, allowing for real-time compensation and unbiased localization, enabling immediate rendering of final localization data during measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If post-processing is used to account for experimental conditions in MINFLUX localization, then measurement precision is improved, but productivity deteriorates due to slower sample optimization and throughput
Solution Approach 1:
The patent pre-calculates and stores calibration data for various experimental conditions (spatial intensity distributions, signal-to-noise ratios) before actual localization. This preliminary action allows the system to bypass time-consuming post-processing by directly applying pre-computed correction factors during real-time localization, thus maintaining high precision while improving throughput
Solution Approach 2:
The system implements real-time feedback by continuously monitoring experimental conditions and dynamically adjusting localization parameters based on pre-calibrated data. This feedback mechanism enables the system to adapt to varying conditions without requiring iterative post-processing, thereby maintaining measurement precision while significantly reducing processing time and improving sample throughput
2Productivity
If real-time adaptation of estimator is implemented, then productivity is improved through faster sample optimization, but device complexity increases
Solution Approach 1:
The patent pre-calculates and stores calibration data for various experimental conditions (spatial intensity distributions, signal-to-noise ratios) before actual localization. This preliminary action allows the system to bypass time-consuming post-processing by directly applying pre-computed correction factors during real-time localization, thus maintaining high precision while improving throughput
Solution Approach 2:
The system implements dynamic adaptation of localization estimators by continuously monitoring experimental conditions and adjusting parameters in real-time based on pre-calibrated data. This dynamic approach enables the system to adapt to varying conditions without requiring complex iterative post-processing, thereby maintaining measurement precision while significantly reducing processing time and improving sample throughput
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 facilitates real-time unbiased localization, improves sample optimization, and enhances throughput by accurately adjusting photon usage, especially during iterative MINFLUX imaging, and also during molecule tracking.
Implementation Method 1
The sample is illuminated with light at one or more sets of probe positions and fluorescence photons are acquired for the sets of probe positions
Data Source
AI summary
The present invention is related to a method, a computer program, and apparatus for adapting an estimator for use in a microscope for estimating a position of an emitter in a sample based on a method, in which the sample is illuminated with light at one or more sets of probe positions and fluorescence photons are acquired for the sets of probe positions. The invention is further related to a microscope, which makes use of such a method or apparatus. The sample is illuminated with light at one or more sets of probe positions and fluorescence photons are acquired for the sets of probe positions. Photon counts of the acquired photons are then added to vectors of photon counts or sums of photon counts are determined for the sets of probe positions. A value representative of background noise is determined and used for adapting the estimator in real-time.