Rotated Domain Arrays for Microarray Site Registration
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Solution Overview
Problem
Conventional registration methods for patterned arrays are computationally burdensome and prone to errors due to sensitivity issues with large-scale distortions and walk-off errors, particularly in high-density microarrays, which can lead to incorrect site identification and interpretation of biological interactions.
Innovation Solution
The array is divided into domains with rotated layouts, allowing for efficient and robust registration using a locally rigid registration algorithm, which increases sensitivity to local distortions and reduces registration errors by ensuring no two adjacent domains share the same rotation orientation, thus enhancing the accuracy of site identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full registration is used to locate sites by absolute reference, then measurement precision is improved, but device complexity and computational burden increase significantly
Solution Approach 1:
The patent divides the large array into multiple smaller domains, each with its own layout. This segmentation allows the system to use simpler local registration algorithms within each domain while maintaining overall registration accuracy through the domain structure and cross-correlation checks between adjacent domains.
Solution Approach 2:
The patent introduces a rotational dimension to the domain layouts, where adjacent domains have different rotations. This adds a new degree of freedom that helps distinguish between sites and reduces walk-off errors, while the two-dimensional cross-correlation check provides an additional verification dimension without significantly increasing computational complexity.
2Productivity
If rigid registration is used for rapid local registration, then productivity is improved, but measurement precision deteriorates due to insensitivity to local distortions
Solution Approach 1:
The patent applies different registration approaches to different regions. Within each domain, rigid registration is used for rapid processing. Between domains, the system performs cross-correlation checks to detect and correct for local distortions and walk-off errors, thus maintaining precision where needed without sacrificing overall speed.
Solution Approach 2:
The system uses cross-correlation checks between adjacent domains as a feedback mechanism to detect registration errors and walk-off distortions. When errors are detected, the system can correct them by adjusting the registration parameters, thereby maintaining measurement precision while retaining the speed benefits of rigid registration.
3Device complexity
If reliance on local registration is used, then device complexity is reduced, but reliability deteriorates due to walk-off errors and accumulation of registration errors
Solution Approach 1:
The patent introduces asymmetry through rotational layouts of adjacent domains. Since adjacent domains have different rotations, the system can use this asymmetric structure to detect walk-off errors and prevent the accumulation of registration errors. The two-dimensional cross-correlation check leverages this asymmetry to provide reliable site identification.
Solution Approach 2:
The patent uses cross-correlation checks as an intermediary verification step between the registration process and site identification. This intermediary check compares the registered positions with expected positions based on the rotational domain structure, thereby detecting and preventing walk-off errors without requiring complex registration algorithms throughout the entire array.
4Measurement precision
If cross-correlation checks are used to detect walk-off errors, then measurement precision is improved, but computational cost increases
Solution Approach 1:
The patent segments the large array into smaller domains, which reduces the number of pixels and objects that need to be processed in each cross-correlation check. This segmentation significantly decreases the computational energy required for accuracy checks while maintaining the ability to detect walk-off errors throughout the entire array.
Data Source
AI summary
The present techniques provides methods for use in conjunction with an article of manufacture having a plurality of sample sites of an array and to identify sample sites based on image data. The array may be divided into a series of domains with each domain having patterns of sample sites. Neighboring domains may be oriented at different angles such that each domain does not have the same pattern orientation.