Localization Microscopy Depth Displacement Correction
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Solution Overview
Problem
Localization microscopy faces challenges in achieving high resolution due to optical imaging errors like chromatic aberrations and lateral field distortions, which are difficult to correct using conventional methods, especially when imaging structures below 100 nm resolution.
Innovation Solution
The method involves displacing the depth of field range along the optical axis by a predetermined axial z-travel distance, generating multiple sample images, and using lateral x/y-position deviations to generate correction information that corrects for imaging errors, thereby improving localization accuracy without requiring additional calibration or complex apparatus adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional light-microscopic imaging methods are used, then the imaging process is simple, but the resolution is limited by the diffraction-dependent resolution limit (cannot image structures below ~200 nm)
Solution Approach 1:
The imaging process is segmented into multiple sequential steps: (1) stochastic activation of only a sparse subset of fluorescent markers at each time point, (2) localization of individual markers in each subset, (3) repeated imaging with different subsets, and (4) computational reconstruction of the complete high-resolution image from all localized positions. This segmentation allows achieving super-resolution by processing many low-resolution frames to reconstruct a high-resolution image.
Solution Approach 2:
The sample is preliminarily prepared by labeling target structures with photoswitchable or photoactivatable fluorescent markers before imaging. This preliminary marking enables the subsequent stochastic activation and localization steps to achieve super-resolution by tracking individual marker positions over time.
2Measurement precision
If a very large number of individual raw data images are taken to image complex structures, then complete sample structure coverage is achieved, but the acquisition time increases significantly
Solution Approach 1:
The imaging employs periodic cycles of marker activation, imaging, and deactivation. In each cycle, a different sparse subset of markers is stochastically activated and imaged. This periodic repetition with varying subsets allows efficient sampling of the complete sample structure over time, balancing coverage completeness with acquisition speed.
Solution Approach 2:
Instead of attempting to image all markers simultaneously (which would fail due to overlap), the method uses partial action by imaging only a sparse subset of markers at each time point. This partial imaging approach, repeated many times with different subsets, ultimately achieves complete structure coverage while maintaining temporal feasibility.
3Quantity of substance
If the density of markers in the active subset is increased to improve sampling, then more markers are available for imaging, but the average distance between adjacent markers decreases below the resolution limit causing overlap
Solution Approach 1:
The method ensures that at each spatial location, only a limited number of markers (ideally 0 or 1) are active simultaneously. This local sparsity constraint maintains marker distinguishability by preventing overlap, while the global repetition across many frames ensures sufficient sampling of all sample structures through the accumulation of many such sparse snapshots.
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 effectively corrects lateral field distortions and other imaging errors, enhancing the localization accuracy of point objects in three-dimensional structures, even in complex samples, by analyzing position deviations across multiple images and generating correction information for precise positioning.
Implementation Method 1
If for example fluorescent dyes are used as markers, the bright state is a state capable of fluorescence and the dark state is a state incapable of fluorescence
Implementation Method 2
the size of which spot is determined by the resolution limit of the optical unit
Data Source
AI summary
A light-microscopic method of localization microscopy for localizing point objects in a sample arranged in an object space includes imaging, by an imaging optical unit having a depth of field range of predetermined axial z-extension along its optical axis in the object space, the sample onto a detector; localizing the point objects in the sample within the depth of field range in that, on the basis of a sample image, lateral x/y-positions of the point objects in a direction perpendicular to the optical axis are ascertained; displacing, in the object space relative to the sample the depth of field range within which the point objects are localized in the object space relative to the sample along the optical axis at least once by a predetermined axial z-travel distance; and imaging, by the imaging optical unit in the event of an axially displaced depth of field range.