Sequencer Focus Tracking Using Intensity-Independent Fourier Metrics

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Current focus quality assessment methods in nucleic acid sequencing, such as those using Brenner scores, are intensity-dependent and lack robustness due to variations in fluorophore intensity across flow cell surfaces, leading to mischaracterization of focus variations and inconsistency across instruments or within image tiles.

Innovation Solution

A focus quality metric based on intensity-independent Fourier transforms is generated by calculating mean radial intensities from image data, fitting a piece-wise function to the power spectrum, and determining parameters like radial slope, which is used to parameterize a focus model for real-time focus monitoring and correction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If Brenner scores are used for focus quality assessment, then focus measurement can be obtained, but the measurement is intensity-dependent and lacks robustness due to fluorophore intensity variations

Engineering Contradiction:

Improvefocus quality measurementVSAvoidrobustness across instruments and runs

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent transforms the focus assessment from intensity-dependent spatial gradient analysis (Brenner score) to frequency-domain power spectrum analysis. By calculating the power spectrum of the image and analyzing its frequency components, the method extracts focus quality metrics that are invariant to intensity variations, thereby resolving the contradiction between measurement capability and robustness

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces the mechanical/optical intensity-based focus assessment (Brenner gradient calculation) with a spectral analysis approach. Instead of measuring spatial intensity gradients directly, the method uses Fourier transformation to convert spatial information to frequency domain, where focus quality can be assessed through power spectrum characteristics that are insensitive to intensity fluctuations

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If intensity-dependent focus metrics are used, then focus assessment can be performed, but variations in intensity are mischaracterized as focus variations

Engineering Contradiction:

Improvefocus quality assessmentVSAvoidaccurate focus characterization

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent substitutes intensity-based spatial gradient measurement with frequency-domain power spectrum analysis. The power spectrum captures the spatial frequency content of the image, and focus quality is derived from the decay rate of power with frequency rather than from absolute intensity values, thereby eliminating the confounding effect of intensity variations on focus measurement

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If Brenner scores are compared across instruments or flow cells, then focus quality can be evaluated, but the comparison is inconsistent due to non-uniform intensity distribution

Engineering Contradiction:

Improvefocus quality comparisonVSAvoidconsistency across devices

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent changes the measurement parameter from absolute intensity gradients (Brenner score) to relative frequency-domain power distribution. By analyzing how power decreases with increasing spatial frequency in the power spectrum, the method obtains a focus metric that reflects optical quality rather than intensity magnitude, enabling consistent comparison across different instruments and flow cells

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces direct intensity comparison across devices with frequency-domain power spectrum comparison. The power spectrum transformation converts device-specific intensity characteristics into universal frequency response patterns, allowing meaningful cross-device focus quality evaluation that is independent of intensity non-uniformities

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

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

The intensity-independent focus quality metric provides consistent focus quality measurement across sequencing runs and devices, enabling robust focus tracking and correction, even with photobleaching or intensity fluctuations, thereby improving sequencing accuracy.

Implementation Method 1

processing all or part (e.g., a sub-region or sub-image) to generate a Fourier transform of the respective image data

Methodology Applied

Scientific EffectFourier transform:

Implementation Method 2

subsequently used to determine a power spectrum for the Fourier transform and underlying image data

Methodology Applied

Scientific EffectPower spectrum analysis:

Data Source

PatentUS12566125B2Sequencer focus quality metrics and focus tracking for periodically patterned surfaces

Publication Date: 2026.03.03 ILLUMINA INC

AI summary

Generation and use of a focus quality metric that is intensity independent is described. In one example, the focus quality metric is generated by acquiring an image, such as an image of a patterned surface of a flow cell, and processing all or part (e.g., a sub-region or sub-image) to generate a Fourier transform of the respective image data. By way of example, in one embodiment a discrete Fourier transform may be applied to a sub-region of an image of a patterned flow cell surface. A focus quality metric that is intensity independent may be derived from the Fourier transform of the image data.