Phasor-Based Lifetime Unmixing for Fluorescence Microscopy
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Solution Overview
Problem
Fluorescence microscopy faces challenges in accurately interpreting multicolor images due to spectral overlap and crosstalk, where conventional phasor approaches are not reproducible and require extensive a priori knowledge, and AI/ML methods are not universally applicable.
Innovation Solution
A processor for lifetime-based unmixing that partitions images into segments, evaluates photon counts, determines regions of interest, and generates disjunct lifetime classes through iterative classification, enabling automated fluorophore unmixing without prior knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If lifetime-based unmixing is used to identify fluorophores, then measurement precision is improved, but device complexity increases due to extensive a priori knowledge requirements
Solution Approach 1:
The system performs self-service by automatically determining fluorophore lifetimes from the image data itself without requiring external a priori knowledge. The processor extracts lifetime information directly from the photon arrival time data, making the system independent of pre-programmed fluorophore characteristics and enabling automated analysis.
Solution Approach 2:
The invention changes the approach from using spectral information to using temporal parameters (photon arrival times) for fluorophore identification. By analyzing the time distribution of photon arrivals rather than wavelength information, the system achieves unmixing based on lifetime differences, fundamentally altering the measurement parameter used for discrimination.
2Ease of operation
If conventional phasor approach is used for data visualization, then ease of operation is improved, but measurement precision deteriorates due to inability to resolve individual fluorophores in complex samples
Solution Approach 1:
The system segments the image data by dividing it into multiple image segments and further into pixel groups based on photon arrival time characteristics. This hierarchical segmentation allows the phasor approach to be applied to specific subsets of data, enabling resolution of individual fluorophore contributions within complex mixtures while maintaining the visual simplicity of phasor plots.
Solution Approach 2:
The invention adds a temporal dimension to the conventional phasor approach by incorporating photon arrival time information into the analysis. While conventional phasor plots use only intensity and lifetime magnitude, this system utilizes the full temporal distribution of photon arrivals, effectively adding another dimension of information to distinguish between fluorophores with similar lifetimes.
3Productivity
If fitting approaches are used to determine average fluorescence lifetime, then productivity is improved, but measurement precision deteriorates when more than two fluorophores or multi-exponential behavior is present
Solution Approach 1:
The system replaces the mechanical fitting process with a statistical analysis method based on photon arrival time distributions. Instead of iteratively adjusting parameters to minimize residuals, the system uses maximum likelihood estimation and phasor analysis to directly determine fluorophore lifetimes from the raw time-correlated single-photon counting data, achieving both speed and accuracy.
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
Enables reliable and automated fluorophore unmixing by detecting distinct fluorescence lifetime classes, reducing data complexity, and providing precise channel unmixing in fluorescence microscopy.
Implementation Method 1
Fluorescence-lifetime imaging microscopy (FLIM) is a specific imaging technique which can be used to identify a fluorophore in a sample by determining a decay rate of photons emitted by the fluorophore
Implementation Method 2
A phasor transform that is applied to a histogram representing photon counts as a function of arrival times yields two quantities which are mapped to a two-dimensional space called phasor space
Data Source
AI summary
A processor for lifetime-based unmixing in fluorescence microscopy is configured to acquire an image having a plurality of pixels, each pixel providing information on photon count and photon arrival times, generate a phasor plot that is a vector space representation of the image, partition the image into image segments, evaluate the image segments according to total photon counts of the corresponding subsets of pixels, and execute a lifetime classification by selecting an image segment having a largest total photon count, determining a region of interest in the image encompassing the image segment, determining a phasor subset in the phasor plot corresponding to the region of interest, and generating a lifetime class including a set of image segments corresponding to the phasor subset. A plurality of lifetime classes is generated by iteratively executing the lifetime classification. The processor is configured to perform lifetime-based unmixing using the life-time classes.