Sample Image Registration Using Fiducials for Spatial Mapping
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Solution Overview
Problem
Existing methods fail to provide spatial context for analyte data from biological samples, particularly in determining the position of single cells within a tissue, limiting the assessment of spatial heterogeneity and transcriptomic activity.
Innovation Solution
A method and system for aligning sample images with array images using fiducials to register and generate aligned images, incorporating sample and array fiducials for precise spatial mapping of analyte levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image registration methods are used to align sample images with array images, then spatial mapping accuracy is improved, but the complexity of the system increases due to the need for fiducials and registration algorithms
Solution Approach 1:
Fiducials are placed on both the sample substrate and array substrate before the actual imaging and registration process. This preliminary positioning of reference markers enables subsequent automated alignment without requiring complex real-time adjustments during the main experiment.
Solution Approach 2:
Fiducials serve as intermediary reference objects that mediate between the sample image and array image. These fiducial markers provide common reference points that the registration algorithm can use to calculate transformation parameters, bridging the two different coordinate systems.
2Measurement precision
If high-resolution sample imaging is performed to capture detailed cell morphology, then spatial heterogeneity assessment is improved, but the time required for image acquisition and processing increases
Solution Approach 1:
The imaging process is divided into two segments: first acquiring lower-resolution overview images for alignment purposes, then acquiring higher-resolution images only for the regions of interest. This segmentation allows the system to obtain detailed cell morphology data without the time penalty of imaging the entire sample area at high resolution.
Solution Approach 2:
The system performs partial high-resolution imaging only where needed for spatial heterogeneity assessment, rather than imaging the entire sample at maximum resolution. The registration process enables accurate spatial mapping using a subset of the data at high resolution, reducing overall processing time while maintaining measurement precision.
Data Source
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AI summary
A method for aligning a sample to an array is provided. An image of sample image of a sample can be received by a data processor. The sample image having a first resolution. An array image including an overlay of an array with the sample and an array fiducial can be received by the data processor. The array image having a second resolution lower than the first resolution of the sample image. The sample image can be regisered to the array image by aligning the sample image and the array image. An aligned image can be generated based on the registering. The aligned image can can include an overlay of the sample image with the array. The aligned image can be provided by the data processor. A method for detecing fiducials associated with an array is provided. Systems and non-transitory computer readable mediums performing the method are also provided.