Digital Array Feature Counting via Stochastic Labeling
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Solution Overview
Problem
Current optical imaging systems for arrays are inefficient in imaging multiple regions simultaneously and suffer from instrumental drift and analysis errors in determining target molecule binding, limiting the accuracy and throughput of biomedical data acquisition.
Innovation Solution
An imaging platform with an optical instrument and processor that uses stochastic labeling techniques to digitally count labeled features on arrays, performing image analysis to calculate the number of target molecules by measuring signal and local background intensities, and applying dynamic signal intensity thresholds to discriminate between labeled and non-labeled features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing optical imaging systems image one region of an array at a time, then image analysis accuracy is maintained, but imaging throughput and efficiency deteriorate
Solution Approach 1:
The array is divided into multiple discrete regions that can be independently imaged. The system sequentially captures images of different regions and uses software to stitch them together, enabling parallel processing of multiple regions while maintaining analytical accuracy through region-by-region analysis.
Solution Approach 2:
The imaging system continuously acquires data across multiple regions without idle time between measurements. The sequential imaging process maintains continuous useful action by immediately processing each region's data while preparing for the next region, maximizing throughput without sacrificing analysis quality.
2Measurement precision
If current methods determine signal intensity level for each array feature, then quantitative data extraction is achieved, but instrumental drift and analysis errors increase
Solution Approach 1:
The system incorporates reference features with known signal intensities across the array. These reference points provide feedback for calibrating and normalizing measurements across different regions and time points, compensating for instrumental drift and ensuring consistent quantitative results throughout the imaging process.
Solution Approach 2:
Multiple identical reference features are distributed across different regions of the array. These replicated reference elements serve as consistent benchmarks for comparing signal intensities across regions, enabling the system to detect and correct for variations in imaging conditions and maintain reliable quantitative measurements.
3Measurement precision
If optical labels and scanning techniques are used to detect binding events, then target molecule detection is achieved, but imaging time and processing duration increase
Solution Approach 1:
The imaging system uses periodic scanning of multiple regions in a systematic sequence rather than continuous scanning of a single region. This periodic action across distributed regions reduces total imaging time while maintaining detection sensitivity by capturing all necessary data points through structured, repeated measurements of different array portions.
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
This approach enables simultaneous imaging of multiple array regions, reduces errors, and provides more accurate and quantitative data on target molecule presence, enhancing the efficiency and reliability of biomedical studies.
Implementation Method 1
In some embodiments, the image generated by the optical instrument is a fluorescence image.
Implementation Method 2
In some embodiments, the image generated by the optical instrument is a phosphorescence image.
Implementation Method 3
In some embodiments, the image generated by the optical instrument is a transmitted light, reflected light, or scattered light image.
Data Source
AI summary
Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.