Optical Sectioning via Hybrid Structured and Uniform Illumination
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Solution Overview
Problem
Current imaging techniques, such as wide-field fluorescence microscopy, struggle with optical sectioning of in-vivo structures due to their inability to reject out-of-focus background, leading to low signal contrast and artifacts from movement, while dynamic speckle illumination is slow and prone to striped appearances.
Innovation Solution
A method combining structured and uniform illumination image data sets to create an optically sectioned image, where high-frequency in-focus data from uniform illumination and low-frequency in-focus data from structured illumination are processed and fused to produce a full-resolution image, eliminating out-of-focus content and compensating for noise and object contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wide-field fluorescence microscopy is used, then the imaging process is simple and fast, but out-of-focus background structures cannot be rejected leading to low signal contrast
Solution Approach 1:
The imaging process is segmented into multiple acquisitions with different illumination patterns (structured and uniform). Each pattern captures different frequency components of the image, which are then processed separately and combined to achieve both optical sectioning and high speed
Solution Approach 2:
The system uses periodic switching between structured illumination patterns and uniform illumination patterns. This periodic action enables the capture of multiple frequency components in rapid succession, allowing optical sectioning to be achieved without sacrificing imaging speed
2Measurement precision
If dynamic speckle illumination is used to obtain optical sectioning, then out-of-focus background is rejected, but the imaging process becomes slow requiring several tens of images
Solution Approach 1:
The patent merges structured illumination imaging and uniform illumination imaging into a hybrid approach. The structured illumination provides optical sectioning for low frequencies while uniform illumination captures high frequencies, and both are combined in the frequency domain to achieve fast optical sectioning
Solution Approach 2:
By periodically switching between structured and uniform illumination patterns, the system captures multiple frequency components in rapid succession, reducing the number of images needed from tens (in dynamic speckle) to just a few while maintaining optical sectioning quality
3Measurement precision
If grid pattern illumination is used, then optical sectioning is achieved, but motion artifacts cause striped appearance and misregistration
Solution Approach 1:
The patent applies grid pattern illumination only partially - specifically for capturing low-frequency components with optical sectioning. High-frequency components are captured using uniform illumination, which is less sensitive to motion artifacts. This partial application of grid illumination reduces the impact of motion-related striped artifacts
Solution Approach 2:
The frequency spectrum is segmented into low-frequency and high-frequency components. Low frequencies are processed with structured illumination for optical sectioning while high frequencies use uniform illumination to avoid motion artifacts, and the segments are combined in the frequency domain
4Measurement precision
If structured illumination is used for low-frequency components, then optical sectioning is achieved, but high-frequency details are lost
Solution Approach 1:
The frequency spectrum is segmented into low-frequency and high-frequency components. Each segment is processed with the most appropriate illumination type: structured illumination for low frequencies to achieve optical sectioning, and uniform illumination for high frequencies to preserve resolution details
Solution Approach 2:
The patent transitions from spatial domain processing to frequency domain processing. By transforming the image data into the frequency domain, it becomes possible to selectively combine low-frequency and high-frequency components from different illumination types, achieving both optical sectioning and high-frequency preservation
Data Source
AI summary
A first image data set of the real-world object is received at a processor where the real-world object was illuminated with substantially uniform illumination. A second image data set of the real-world object is received at the processor where the real-world object was illuminated with substantially structured illumination. A high pass filter is applied to the first-image data set to remove out-of-focus content and retrieve high-frequency in-focus content. The local contrast of the second-image data set is determined producing a low resolution local contrast data set. The local contrast provides a low resolution estimate of the in-focus content in the first-image data set. A low pass filter is applied to the estimated low resolution in-focus data set, thus making its frequency information complementary to the high-frequency in-focus data set. The low and high frequency in-focus data sets are combined to produce an optically-sectioned data set of the real-world object.