Local Fiducial Registration for Stage Jitter Image Correction
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Solution Overview
Problem
High frequency motion of a stage (jitter) in line scanning systems induces non-linear perturbations in sequencing images, affecting the accuracy of spot locations and fiducial positions, which compromises data quality in nucleotide sequencing.
Innovation Solution
An image detection device corrects for high frequency jitter by dividing images into sub-regions, performing geometric transforms on each sub-region to register fiducial locations, and adjusting for jitter, using fiducial patterns to determine accurate spot positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to correct jitter, then computational complexity increases and processing time extends, but real-time processing capability is lost
Solution Approach 1:
The system performs preliminary action by capturing a reference image before the actual imaging process. This reference image is used to calculate the jitter correction matrix in advance, allowing real-time correction during actual imaging without extensive processing delays. The reference image serves as a pre-computed foundation for subsequent corrections.
Solution Approach 2:
The patent uses a reference image as a copy or representation of the ideal stable image state. By comparing the actual moving image against this reference copy, the system can calculate correction matrices efficiently. The reference image acts as a template that enables rapid comparison and correction without requiring complex real-time analysis of each image frame.
2Reliability
If multiple images are averaged to reduce jitter, then image processing time increases, but real-time processing is required
Solution Approach 1:
The patent extracts only the essential stable features from images by using a reference image to represent the ideal state. Instead of processing and averaging multiple complete images, the system extracts correction information by comparing actual images against the reference, taking out only the necessary correction data rather than processing entire image sets.
Solution Approach 2:
The reference image is captured and processed in advance to establish the baseline for comparison. This preliminary action allows the system to quickly compute correction matrices during actual imaging without needing to perform complex averaging operations in real-time, thus maintaining both reliability and processing speed.
3Measurement precision
If complex algorithms are used for jitter correction, then correction precision improves, but device complexity increases
Solution Approach 1:
The patent uses a reference image as a simplified copy or model of the ideal stable image. By comparing actual images against this reference copy using straightforward subtraction and matrix operations, the system achieves accurate jitter correction without requiring complex algorithms. The reference copy serves as a simple yet effective benchmark for correction calculations.
Solution Approach 2:
The patent replaces complex mechanical or computational correction systems with a mathematical matrix operation approach. Instead of using complex hardware stabilization mechanisms or sophisticated real-time algorithms, the system uses simple matrix multiplication and subtraction operations on image data, achieving high precision with minimal computational complexity.
4Manufacturing precision
If image processing operations are extended to maintain quality, then processing time increases, but real-time capability is required
Solution Approach 1:
The reference image is captured and prepared in advance, establishing the quality baseline before actual imaging. This preliminary action allows subsequent real-time corrections to maintain image quality through simple matrix operations rather than requiring extended processing operations during critical imaging moments.
Solution Approach 2:
The patent replaces complex image processing operations with efficient matrix mathematics. By substituting elaborate filtering, averaging, or enhancement operations with direct matrix multiplication and subtraction against a reference, the system maintains image quality while dramatically reducing processing duration to enable real-time capability.
Data Source
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AI summary
Systems, methods, and apparatuses are described herein. For instance, a detection apparatus may comprise memory and at least one processor. The detection apparatus may be configured to obtain an image comprising at least one feature and a plurality of fiducials. The plurality of fiducials may be arranged in a pattern. The detection apparatus may be configured to determine a plurality of sub-regions of the image. Each sub-region comprises a subset of the fiducials comprised in the image. The detection apparatus may be configured to perform a geometric transform on each sub-region to generate a respective local transform associated with each sub-region. The detection apparatus may be configured to register respective locations of the fiducials comprised in the image based on the respective local transform associated with each sub-region. A size of each sub-region may be selected such that each sub-region is substantially invariant to stage jitter.