Same-Field Image Reconstruction for Diffraction-Limited Resolution
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Solution Overview
Problem
Mainstream Massive Parallel Sequencing (MPS) technologies are limited by optical diffraction, restricting image resolution and sequencing throughput in optical microscopic imaging systems.
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 enhance resolution, using 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 achieved, but image resolution is limited by optical diffraction
Solution Approach 1:
The patent transitions from direct spatial imaging to frequency domain processing by acquiring multiple raw images at different spatial frequencies and reconstructing the high-resolution image through inverse Fourier transformation. This dimensional transformation in the frequency domain enables super-resolution imaging that overcomes the optical diffraction limit.
Solution Approach 2:
The patent segments the imaging process into multiple acquisitions at different spatial frequencies rather than attempting to capture the full resolution image in a single shot. By dividing the frequency spectrum into multiple bands and reconstructing them collectively, the system achieves resolution beyond the diffraction limit of individual optical paths.
2Measurement precision
If multiple raw images are acquired for reconstruction, then image resolution improves, but the number of images required increases
Solution Approach 1:
The patent performs preliminary actions by acquiring multiple raw images at different spatial frequencies before the final reconstruction step. These pre-acquired images are stored and processed together in the frequency domain, enabling efficient super-resolution reconstruction without requiring excessive numbers of images.
Solution Approach 2:
The reconstruction process uses feedback from the Fourier transformation of acquired raw images to iteratively improve the high-resolution image. The system analyzes the frequency components of acquired images and adjusts the reconstruction accordingly, optimizing the balance between the number of input images and the achieved resolution.
Data Source
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.