Temporal Filtering for High-Density Localisation Microscopy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current localisation microscopy techniques face challenges in achieving high density imaging due to overlapping emitter fluorescence patterns, leading to image artefacts such as artificial sharpening and false clustering, especially when the distance between active emitters is less than the point spread function, which limits the ability to accurately reconstruct sample structures.
Innovation Solution
The method employs multiple time-scale sliding temporal filters to reduce the density of emitters in image frames by exploiting temporal redundancies, allowing for the separation of overlapping emitter fluorescence based on different emission or fluorescence times, thereby enabling accurate localisation without generating image artefacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the number of active emitters per frame is increased to improve imaging speed, then productivity is improved, but measurement precision deteriorates due to overlapping fluorescence patterns
Solution Approach 1:
The patent segments the high-density emitter population into multiple lower-density groups by applying temporal filters that separate emitters based on their blinking characteristics. Each filter identifies a subset of emitters with specific temporal patterns, allowing standard localisation algorithms to accurately process each segment without overlapping interference, while collectively capturing all emitters across multiple filtered datasets.
Solution Approach 2:
The patent introduces dynamic temporal filtering that adapts to the blinking behavior of individual emitters. By using sliding temporal filters with varying time scales, the system dynamically separates emitters based on their unique temporal emission patterns, enabling accurate localisation of high-density emitters that would otherwise overlap spatially.
2Device complexity
If standard single-emitter algorithms are applied to high density data, then device complexity is reduced, but object-generated harmful factors increase due to image artefacts
Solution Approach 1:
The patent applies temporal filtering as a preliminary processing step before standard single-emitter localisation algorithms. This pre-processing separates overlapping emitter signals based on their temporal blinking patterns, ensuring that when simple algorithms are applied to each filtered dataset, they encounter minimal overlapping and generate far fewer artefacts such as artificial sharpening and false clustering.
3Measurement precision
If tens of thousands of image frames are captured to achieve accurate reconstruction, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent introduces temporal filters as an intermediary processing layer between raw image capture and final reconstruction. These filters extract meaningful emitter signals from fewer raw frames by exploiting temporal blinking patterns, effectively acting as a mediator that converts limited spatial-temporal data into high-quality localisation information without requiring tens of thousands of frames.
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 reduces the density of emitters in each frame, allowing for accurate localisation and high-resolution reconstruction without artefacts, enabling the capture of dynamic changes in samples like live cells by increasing the number of active emitters per frame, thus overcoming the limitations of standard single-emitter algorithms.
Implementation Method 1
fluorescent molecules that display fluorescence intermittency or 'blinking'
Implementation Method 2
Photo Activatable Localisation Microscopy (PALM) uses fluorescent proteins to label the structure which can be switched from a non-emitting state into an emitting state by the application of short wavelength visible/near UV light
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Embodiments of the present invention provide a method and system for processing microscopy images to enable localisation analysis of high density raw data, and thereby achieve higher spatial resolution than would otherwise be the case. This is achieved by exploiting temporal redundancies in the image data resulting from close-to emitters that would otherwise be resolved as a single emitter were they to emit or fluoresce at the same time, but which, by virtue of emitting or fluorescing at slightly different (yet potentially overlapping) times, can be subject to temporal filtering by different filters of different temporal bandwidth to resolve the two emitters. Effectively, the different temporal filters have different time constants which work together to effectively highlight the different emission or fluorescence times of the two emitters, to thereby allow the two close-to emitters to be separately resolved.