Reaction Site Imaging with Real-Time Crosstalk Extraction

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Solution Overview

Problem

Conventional optical systems for biological or chemical analysis face challenges in managing unwanted light emissions (crosstalk) as the density of analytes increases, particularly in systems using charged-coupled devices or complementary metal-oxide-semiconductor detectors.

Innovation Solution

A method and system for determining point spread functions to compensate for crosstalk by obtaining noise dependencies, generating a sharpening kernel, and applying it to analysis images to enhance signal-to-noise ratio, using a sensor array and processor to iteratively refine the kernel for optimal performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If the density of analytes is increased to improve assay throughput and information content, then productivity and measurement capability are improved, but crosstalk from adjacent analytes increases causing measurement precision to deteriorate

Engineering Contradiction:

Improveassay throughputVSAvoidsignal accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent converts the harmful crosstalk signal into useful information by using it to train a machine learning model. The neural network learns to distinguish true analyte signals from crosstalk artifacts by analyzing training images that contain both types of signals, ultimately improving measurement precision while maintaining high analyte density

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The patent introduces a machine learning model as an intermediary between the raw imaging data and the final measurement results. This intermediary processes the complex images containing crosstalk, extracts meaningful signals, and provides corrected measurements, thereby resolving the contradiction between high density and measurement accuracy

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If conventional optical systems with lenses and filters are used to reduce crosstalk, then measurement precision is improved, but device complexity and cost increase

Engineering Contradiction:

Improvesignal accuracyVSAvoidoptical assembly complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical/optical system (lenses, filters, and other physical components) with a computational system based on machine learning. Instead of using physical means to reduce crosstalk, the system uses algorithms to identify and correct crosstalk artifacts in the captured images, thereby reducing device complexity while maintaining measurement precision

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent creates computational models and simulations of the optical system's behavior to understand and correct crosstalk effects. By modeling the point spread function and crosstalk patterns computationally, the system can reverse-engineer and correct the effects without needing complex physical optical components

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260017795A1Methods and systems for real time extraction of crosstalk in illumination emitted from reaction sites

Publication Date: 2026.01.15 ILLUMINA INC

AI summary

Biosensor including an array of reaction sites and corresponding light sensors may experience crosstalk in which photons from one reaction site are detected by neighbors of its corresponding light sensor, and such crosstalk may be corrected using sharpening kernels corresponding to the sensors in the array. Such sharpening kernels may be derived from point spread functions, which may be determined in real time analysis based on images captured during sequencing.