Imaging System Self-Test for Spatial Registration Accuracy
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Solution Overview
Problem
Existing methods for analyzing spatial heterogeneity in biological samples fail to accurately register image data with sequence data, lacking effective methods for aligning spatial and transcriptomic information within a sample.
Innovation Solution
A method for self-testing an imaging system in a sample handling apparatus, which includes mounting a self-test slide with a pattern featuring an array of first features and a reference side rotated at a non-zero angle. The system acquires image data, determines linear and non-linear distortion errors, and compares these to registration error thresholds to output annunciations for system adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image registration methods are used to align image data with sequence data, then spatial mapping accuracy is improved, but system reliability deteriorates due to untested optical distortion errors
Solution Approach 1:
The patent applies preliminary action by performing self-tests on the imaging system before actual sample analysis. The system acquires test images of a patterned slide, determines distortion parameters, and stores calibration data in advance. This preliminary calibration ensures that when real samples are analyzed, the registration accuracy is maintained without introducing reliability issues from untested optical errors.
Solution Approach 2:
The patent implements feedback by continuously monitoring optical distortion through self-tests and using the results to adjust or validate the registration process. The system compares measured distortion parameters against stored calibration values and can trigger re-calibration or alert operators when distortion exceeds acceptable thresholds, thereby maintaining both precision and reliability.
2Reliability
If self-test procedures are implemented to ensure imaging accuracy, then system reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies self-service by enabling the imaging system to automatically perform self-diagnosis and self-calibration using a specialized test slide. The system independently acquires test images, processes distortion parameters, and generates calibration data without requiring external intervention. This automated self-testing reduces the need for manual calibration procedures and external quality control equipment, thereby improving reliability while limiting the increase in device complexity.
Solution Approach 2:
The patent implements universality by designing a multi-functional self-test slide that serves multiple purposes: it acts as an optical calibration target, a distortion measurement reference, and a system performance validation tool. This single component enables the system to test various imaging parameters including focus, distortion, and registration accuracy, reducing the need for multiple separate calibration devices.
3Measurement precision
If distortion parameters are determined and compared to thresholds, then measurement precision is improved, but loss of time increases due to additional testing steps
Solution Approach 1:
The patent applies preliminary action by performing distortion parameter determination and threshold comparison during system setup or periodic self-tests, rather than during each sample analysis. The calibration data is stored in advance and reused for multiple samples, eliminating the need to repeat time-consuming distortion measurements for each analysis, thus improving precision without proportionally increasing time loss.
Solution Approach 2:
The patent implements continuity of useful action by establishing a periodic self-test schedule that maintains calibration validity without interrupting continuous sample processing. The system can perform rapid self-tests during idle periods or between samples, ensuring distortion parameters remain current while minimizing time loss. The stored calibration data enables continuous sample analysis without repeated time-consuming calibration steps.
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 method ensures accurate alignment and registration of image and sequence data, enhancing the precision of spatial heterogeneity analysis and transcriptomic activity mapping within biological samples.
Implementation Method 1
acquiring, by the image sensor, image data representing a single image of the pattern
Data Source
AI summary
A method of self-testing an imaging system of a sample handling apparatus is provided. Systems and non-transitory computer readable mediums performing the method are also provided.