Image-Based Autofocus Using Single-Image Z-Shift Detection
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Solution Overview
Problem
Existing autofocus methods for fluorescence-based genomic testing assays require dedicated hardware such as AF lasers and sensors, increasing machinery costs and complexity, and often rely on multiple images, leading to increased time and computational complexity.
Innovation Solution
An image-based autofocusing method that utilizes a single image to determine z-shift for autofocusing, tilting the sample stage or image sensor, and adjusting optical parameters to correct defocus without dedicated AF hardware, reducing computational complexity and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated AF hardware (AF lasers and sensors) is used for autofocusing, then autofocus functionality is achieved, but machinery costs and system complexity increase
Solution Approach 1:
The imaging sensor is made multi-functional by using it for both fluorescence image acquisition and autofocus determination. The same sensor captures images that serve dual purposes: scientific imaging for genomic analysis and autofocus measurement for optical alignment, eliminating the need for dedicated AF hardware.
Solution Approach 2:
The patent merges the autofocus function with the existing imaging system by combining the autofocus determination process with the fluorescence image acquisition process. The in-focus region analysis is integrated into the standard imaging workflow, consolidating multiple functions into a single system.
2Measurement precision
If multiple images are used for autofocusing, then autofocus accuracy is improved, but time consumption and computational complexity increase
Solution Approach 1:
The image is segmented into in-focus and out-of-focus regions based on intensity thresholding. By dividing the image analysis into distinct regions and using the spatial distribution of in-focus pixels, the system achieves accurate autofocus determination from a single image without requiring multiple images or complex temporal processing.
3Measurement precision
If multiple images are acquired for autofocusing, then focus determination is more accurate, but computational complexity increases
Solution Approach 1:
The patent extracts the in-focus region information from the fluorescence image by applying intensity thresholding and spatial analysis. By extracting only the relevant in-focus pixel data and using its distance distribution from the image center, the system achieves accurate focus determination with minimal computational processing of a single image.
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
Achieves accurate autofocusing with an error range of less than 100 nm, reducing machinery costs and complexity while minimizing photo bleaching, and completing autofocusing in under 500 milliseconds.
Implementation Method 1
obtaining, by an image sensor of the optical system, an image of the sample on the tilted sample stage
Data Source
AI summary
The present disclosure describes illumination methods and systems for illumination as well as methods and systems for autofocusing the systems. The systems can be used for, for example, microscopy and sequencing platforms. The methods and systems of the present disclosure can provide fast and accurate autofocusing, which can reduce error and improve system throughput.