Bright Spot Detection for Weak Nucleic Acid Sequencing Images
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Solution Overview
Problem
Current methods for spot detection in nucleic acid sequencing, particularly in third-generation sequencing, face challenges due to the use of random sequencing chips and weak, interfered signals, making accurate identification and location of nucleic acid molecules difficult.
Innovation Solution
A method and device for detecting spots on images, involving preprocessing, simplification, and threshold-based identification of candidate spots using pixel matrices and connectivity criteria, optimized for both second- and third-generation sequencing platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional spot detection methods are used on random sequencing chip images, then the detection process becomes complex and inaccurate, but implementing complex image processing and thresholding increases computational burden and reduces detection speed
Solution Approach 1:
The patent segments the image processing into distinct stages: background removal, binary thresholding, and spot candidate identification. By dividing the complex detection task into manageable segments with specific operations at each stage, the method achieves high accuracy without overwhelming computational complexity. Each segment processes specific image characteristics independently, making the overall system tractable.
Solution Approach 2:
The patent dynamically adjusts processing parameters including threshold values, pixel connectivity requirements, and spot size criteria based on image characteristics. By changing parameters adaptively rather than using fixed complex algorithms, the method maintains high detection accuracy across different image types while controlling computational burden through parameter optimization rather than algorithmic complexity.
2Measurement precision
If complex image processing is applied to identify spots with weak signals, then detection accuracy improves, but processing time increases and throughput decreases
Solution Approach 1:
The patent performs preliminary background removal and binary thresholding operations before spot identification. By preparing the image in advance with these preprocessing steps, the actual spot detection operates on simplified binary data rather than raw grayscale images, significantly reducing processing time for each spot while maintaining accuracy for weak signals.
Solution Approach 2:
The patent extracts only the essential features needed for spot detection: binary pixel values and connectivity information. By taking out and focusing only on these critical characteristics rather than processing the entire image data, the method achieves high signal identification accuracy while minimizing processing overhead and maximizing throughput.
3Reliability
If strict pixel connectivity criteria are enforced to eliminate false positives, then detection reliability improves, but some valid weak spots may be missed reducing sensitivity
Solution Approach 1:
The patent applies different connectivity requirements locally based on spot characteristics and image regions. Rather than enforcing uniform strict criteria throughout the entire image, the method adjusts connectivity thresholds locally to match expected spot patterns in different areas, maintaining high reliability in regions with strong signals while preserving sensitivity for weak spots in other regions.
Data Source
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AI summary
A method and device for detecting bright spots on an image. The so-called image is acquired from a field of view where a base extension reaction occurs, multiple nucleic acid molecules with optically detectable labels exist in the field of view where the base extension reaction occurs, and at least some of the nucleic acid molecules appear as bright spots on the image. The method comprises: preprocessing the image to obtain a preprocessed image (S10); determining a critical value to simplify the preprocessed image to obtain a simplified image (S20); determining a first bright spot detection threshold c1 on the basis of the preprocessed image (S30); and identifying candidate bright spots on the image on the basis of the preprocessed image and the simplified image, including determining a pixel matrix that satisfies at least two of conditions a)-c) as a candidate bright spot (S40). The method can quickly and effectively implement accurate detection of bright spots on images, especially for images acquired from nucleic acid sequence determination reactions.