Conical Diffraction Superresolution Imaging via Bayesian Reconstruction
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Solution Overview
Problem
Existing superresolution microscopy techniques face limitations in achieving high precision, are complex to operate, and lack the simplicity and robustness of standard microscopes, making them unsuitable for general research or diagnostic tools, particularly failing to detect and quantify multiple fluorophores in the same illuminated volume and lacking the ability to perform in-vivo diagnostics.
Innovation Solution
An optical measurement method using two lasers with controlled polarization states, where one laser is tuned to the excitation wavelength and the other to the depletion wavelength, combined with achromatic projection and conical diffraction, allows for precise determination of the spatial distribution and location of re-emitting sources, enabling high-resolution imaging beyond the diffraction limit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing superresolution microscopy techniques are used, then resolution beyond the diffraction limit is achieved, but the system becomes complex to operate and loses simplicity and robustness
Solution Approach 1:
The patent segments the complex superresolution problem into distinct functional modules: excitation light source, depletion light source, conical diffraction element, and detection system. Each module performs a specific function, making the overall system easier to operate while maintaining high precision spatial distribution determination
Solution Approach 2:
The patent introduces a conical diffraction element as an intermediary component that transforms the light fields in a controlled manner. This intermediary enables superresolution without requiring complex computational algorithms or multiple sequential measurements, thereby maintaining operational simplicity
2Measurement precision
If existing superresolution techniques are used, then high resolution imaging is achieved, but the system fails to detect and quantify multiple fluorophores in the same illuminated volume
Solution Approach 1:
The patent uses conical diffraction to create structured light fields with specific spatial distributions that encode information about multiple fluorophores. By manipulating the light field in multiple dimensions (spatial, angular, and spectral), the system can simultaneously detect and quantify multiple fluorophores in the same illuminated volume while maintaining high spatial precision
Solution Approach 2:
The patent employs parameter changes in the light field (intensity, polarization, wavelength) to selectively excite and deplete different fluorophores. By varying these parameters, the system can distinguish between multiple fluorophores and determine their spatial distributions independently, enhancing both precision and versatility
3Measurement precision
If complex superresolution systems are used, then high precision imaging is achieved, but the system is not suitable for general research or diagnostic tools and lacks robustness
Solution Approach 1:
The patent designs a system where the conical diffraction element automatically performs the complex light field transformations required for superresolution without requiring external control or adjustment. This self-service approach reduces operational complexity and increases system robustness, making it suitable for general research and diagnostic applications
Solution Approach 2:
The patent uses homogeneous optical components and standardized procedures that can be easily replicated across different laboratories and applications. This homogeneity ensures consistent high-precision performance and increases system reliability for general use
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 method enhances the precision of superresolution imaging, simplifies the operation, and enables the detection of multiple fluorophores, as well as potential in-vivo diagnostic capabilities, reducing the need for biopsies and shortening patient waiting times.
Implementation Method 1
the projection, by means of an achromatic projection optical device, for each laser of a compact light distribution propagating along the same optical path; the use of conical diffraction
Implementation Method 2
the wavelength of one of the lasers being tuned to the excitation wavelength of said at least one re-emitting source
Implementation Method 3
the wavelength of the second laser being tuned to the depletion or activation wavelength of said at least one re-emitting source
Implementation Method 4
the realization, using a polarization sub-module, for each laser, of a controlled polarization state
Data Source
Figure 1
Figure 2
Figure 3~4a
AI summary
The optical and/or optoelectronic system includes a cone diffraction-based super-resolution fluorescence imaging system incorporating a Bayesian reconstruction algorithm. The formulation of the object reconstruction and its spatial, temporal, and/or spectral properties is considered an inverse Bayesian problem, leading to the definition of a posterior distribution. The estimation of the light distribution within the sample is performed using point emitter clouds, which favors sparse solutions. The posterior mean estimation is carried out using a Markov Chain Monte Carlo (MCMC) algorithm.