Probe Array Imaging Resolution via Micro-Shifted Image Reconstruction
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Solution Overview
Problem
Existing systems face challenges in accurately analyzing small feature sizes on probe arrays due to sources of error from scanning systems, such as blurring caused by large spot sizes compared to the size of probe features, which complicates the analysis of biological data from arrays like Affymetrix GeneChip arrays.
Innovation Solution
The method involves acquiring micro-shifted images of a probe array, reconstructing an image, and deriving intensity values for probe features, using techniques like Simple Image Interlace (SII) and unboxing algorithms to enhance resolution and accuracy, particularly for features smaller than 1 μm in size.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a light source is focused to a spot and scanned across the probe array, then the scanning system can capture images of the probe array, but the large spot size produces blurring in the resulting image
Solution Approach 1:
The patent divides the image acquisition process into multiple micro-shifted images captured at different sub-pixel positions. By segmenting the imaging process into multiple discrete measurements and combining them through reconstruction algorithms, the system achieves super-resolution imaging that overcomes the blurring effect of the large spot size.
Solution Approach 2:
The patent introduces an additional dimension of measurement by capturing images at multiple micro-shifted positions (sub-pixel displacements) in addition to the standard pixel grid. This multi-dimensional data acquisition enables reconstruction algorithms to extract higher resolution information than the original spot size would permit.
2Productivity
If the scanning system uses a large spot size, then the scanning speed and coverage area are improved, but the analysis accuracy of small probe features deteriorates
Solution Approach 1:
The patent performs preliminary actions by capturing multiple micro-shifted images at different sub-pixel positions before final reconstruction. This pre-acquisition of redundant data at high speed allows subsequent reconstruction algorithms to extract precise feature measurements that would be impossible from a single blurred image.
Solution Approach 2:
The patent creates multiple copies of the probe array image at different micro-shifted positions. These replicated images, captured rapidly by the scanning system, are then processed through reconstruction algorithms to generate a high-resolution composite that preserves feature accuracy while maintaining scanning efficiency.
3Measurement precision
If images are acquired at multiple micro-shifted positions, then the reconstructed image resolution is improved, but the complexity of the image processing system increases
Solution Approach 1:
The patent implements self-service by using the redundant information inherently present in the multiple micro-shifted images to automatically resolve the resolution limitation. The reconstruction algorithms utilize the overlapping information from different positions to self-correct the blurring effect without requiring external calibration or complex hardware modifications.
Solution Approach 2:
The patent replaces complex mechanical resolution improvement systems with computational reconstruction methods. Instead of using multiple physical objectives or complex optical arrangements, the system uses software-based reconstruction algorithms to achieve super-resolution from relatively simple micro-shifted image acquisitions.
Data Source
AI summary
An embodiment of a method for resolving features on a probe array is described that, comprises acquiring a plurality of micro-shifted images of a region of a probe array; reconstructing an image of the probe array using the micro-shifted images; and deriving intensity values for one or more probe features disposed on the probe array from the reconstructed image.