Imaging Registration for Sparse Signal Extraction in Dense Arrays
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Solution Overview
Problem
Next-generation sequencing methods face challenges in accurately detecting features on polynucleotide arrays due to significant spatial overlap of fluorescent signals between neighboring features, especially as feature sizes approach the optical resolution limit, leading to difficulties in precise detection and analysis.
Innovation Solution
The implementation of image analysis methods and systems that register multiple images of features using an intensity threshold function and a corrugation function to accurately detect and align features, even in high-density arrays, by applying parameter data to correct for distortions and overlapping signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If feature density is increased in polynucleotide arrays, then array capacity and throughput are improved, but spatial overlap of fluorescent signals between neighboring features increases, leading to reduced detection accuracy
Solution Approach 1:
The patent applies segmentation by dividing the detection process into multiple sequential imaging cycles, where each cycle captures signal from a specific subset of features at different spatial positions. This temporal and spatial segmentation allows dense features to be detected individually without signal overlap, resolving the contradiction between high array capacity and detection accuracy
Solution Approach 2:
The patent introduces a temporal dimension to the detection process by implementing sequential imaging across multiple cycles. Features that are spatially overlapping in the array are separated in time through cyclic detection, allowing accurate measurement of each feature's signal intensity without interference from neighboring features
2Quantity of substance
If feature size is reduced to increase array density, then more features can be accommodated on the array, but features approach the optical resolution limit, making accurate detection problematic
Solution Approach 1:
The patent segments the detection of small features into multiple imaging cycles with different spatial selections. By detecting features in sequential cycles rather than attempting to capture all features simultaneously, the system can accurately measure signals from sub-resolution features without overlap interference
Solution Approach 2:
The patent performs preliminary actions by pre-determining which features should be detected in each imaging cycle based on their spatial coordinates. This preliminary planning allows the system to optimize detection parameters and selection criteria before actual imaging, improving accuracy for small features
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
Enhances the accuracy of feature detection and registration in high-density polynucleotide arrays, improving the precision of sequencing data analysis and alignment.
Implementation Method 1
one or more features include a fluorescent emission
Data Source
AI summary
Disclosed herein, inter alia, are methods and systems of image analysis useful for identifying and/or quantifying features associated with biomolecules.