Structured Illumination Particle Detection SAO
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional Synthetic Aperture Optics (SAO) imaging requires a large number of redundant and irrelevant selective excitation patterns, making it impractical for applications like DNA sequencing due to high cost and low throughput, and is mechanically and thermally unstable.
Innovation Solution
The method minimizes the number of selective excitation patterns based on the target's physical characteristics and optical imaging system parameters, using a half-ring arrangement of interference pattern generation modules to optimize SAO for high-resolution imaging with reduced hardware complexity and improved stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a large number of selective excitation patterns are used in conventional SAO imaging, then resolution beyond physical constraints is achieved, but device complexity and cost increase dramatically
Solution Approach 1:
The patent extracts and removes redundant and irrelevant selective excitation patterns from the conventional SAO methodology. By identifying and eliminating unnecessary patterns while retaining only those essential for achieving super-resolution, the system maintains imaging quality while dramatically reducing device complexity and operational cost.
Solution Approach 2:
Instead of applying all possible selective excitation patterns, the patent uses only a minimized subset that is sufficient to achieve the desired resolution. This partial action approach avoids the excessive complexity of conventional methods while still obtaining the necessary spatial frequency information for high-resolution reconstruction.
2Manufacturing precision
If conventional SAO imaging uses many selective excitation patterns, then high-resolution imaging is achieved, but throughput decreases and cost increases
Solution Approach 1:
The patent extracts and eliminates redundant excitation patterns from the conventional SAO process. By removing unnecessary measurement steps while retaining the essential patterns needed for resolution, the system achieves high throughput without sacrificing imaging quality, making it practical for applications like DNA sequencing.
Solution Approach 2:
The patent skips over redundant and irrelevant excitation patterns that do not contribute meaningfully to the final image quality. By jumping directly to the essential patterns and corresponding reconstruction steps, the system dramatically reduces the number of operational cycles required, thereby increasing throughput and reducing cost.
3Loss of information
If conventional SAO imaging implements full selective excitation pattern sets, then complete spatial frequency information is obtained, but mechanical and thermal stability deteriorates
Solution Approach 1:
The patent extracts only the essential selective excitation patterns required to obtain complete spatial frequency information, removing redundant patterns that would require additional mechanical adjustments and time. This minimized set of patterns reduces the cumulative mechanical and thermal disturbances, thereby improving system stability.
Solution Approach 2:
The patent performs preliminary identification and selection of the minimal necessary excitation patterns before actual imaging. By pre-determining which patterns are essential for complete spatial frequency coverage, the system avoids unnecessary mechanical movements and thermal cycles, thereby maintaining better stability throughout the imaging process.
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 enables efficient and cost-effective high-resolution imaging in DNA sequencing by reducing the number of excitation patterns and stabilizing the SAO system, achieving dramatic increases in throughput and reducing costs.
Implementation Method 1
Selective excitation (or illumination) 104 may be applied to the imaging target 102 by an illumination apparatus (not shown in FIGS. 1A and 1B) that is configured to cause interference 122 of two or more light beams 131, 132 on the imaging target 102.
Data Source
AI summary
A particle detection method detects presence and location of particles on a target using measured signals from a plurality of structured illumination patterns. The particle detection method uses measured signals obtained by illuminating the target with structured illumination patterns to detect particles. Specifically, the degree of variation in these measured signals in raw images is calculated to determine whether a particle is present on the target at a particular area of interest.