Microscopy Image Reconstruction Using Multi-Image Illumination Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Optical microscopic imaging systems are limited by the optical diffraction limit, restricting the resolution of acquired images and sequencing throughput in Massive Parallel Sequencing technologies.
Innovation Solution
A method for image reconstruction that involves acquiring multiple raw images of a sample in the same field of view and performing reconstruction to improve image resolution, utilizing a light modulator to regulate illumination light and an apparatus comprising a processor and memory to implement this method.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical microscopic imaging systems are used for Massive Parallel Sequencing, then imaging capability is provided, but image resolution is limited by the optical diffraction limit
Solution Approach 1:
The patent divides the imaging process into multiple raw image acquisitions under different illumination patterns (e.g., different spatial light modulator patterns), then segments the reconstruction process into iterative computational steps. This segmentation allows the system to overcome the diffraction limit by combining information from multiple segmented measurements rather than relying on a single optical measurement.
Solution Approach 2:
The patent transitions from direct spatial domain imaging to frequency domain processing through Fourier transforms. By acquiring images under multiple illumination patterns and processing them in the frequency domain, the system reconstructs super-resolution images that exceed the optical diffraction limit, effectively adding a computational dimension to the traditional optical imaging process.
2Measurement precision
If multiple raw images are acquired for image reconstruction, then image resolution is improved, but the number of raw images required increases processing time
Solution Approach 1:
The patent employs periodic illumination patterns through the spatial light modulator, cycling through different patterns to acquire multiple raw images. This periodic action systematically varies the illumination to encode different spatial frequency information, enabling resolution enhancement while maintaining a structured and efficient acquisition sequence that optimizes processing time.
Solution Approach 2:
The iterative reconstruction algorithm continuously processes the acquired raw images, refining the reconstructed image in each iteration until convergence is achieved. This continuous useful action ensures that the system fully utilizes the information from multiple raw images to progressively improve resolution without unnecessary idle time, optimizing the balance between resolution enhancement and processing efficiency.
Data Source
Figure 1~2(b)
Figure 3(a)~5
Figure 6(a)~8
AI summary
An image reconstruction method and apparatus. The method comprises: acquiring a plurality of original images of a sample under test in a same field of view; and performing image reconstruction according to the plurality of original images in respect of said field of view, so as to obtain a reconstructed image of said field of view. Image reconstruction is performed on the basis of a plurality of original images of a same field of view, so that the image resolution can be improved.