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Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically
Yu Lin1,2, Yan Wang1,3, Juexin Wang4
1School of Artificial Intelligence, Jilin University, Changchun 130012, China.
Cells
|July 11, 2025
Summary
Xenium-Align automatically identifies keypoints for spatial transcriptomics image registration, streamlining data analysis. This method enhances the alignment of gene expression and histology images in Xenium Explorer.
Area of Science:
- Spatial transcriptomics
- Bioinformatics
- Computational pathology
Background:
- Accurate image registration is crucial for integrating spatial transcriptomics data with histology in platforms like 10X Xenium.
- Manual keypoint placement for image alignment in Xenium Explorer is time-consuming and requires expert input.
Purpose of the Study:
- To develop an automated method, Xenium-Align, for generating keypoint files for image registration in Xenium Explorer.
- To reduce the labor intensity of aligning spatial transcriptomics and H&E images.
Main Methods:
- Xenium-Align algorithm for automatic keypoint identification.
- Validation using 14 human kidney and 1 human skin Xenium samples.
- Comparison with manually marked keypoints by domain experts.
Main Results:
- Xenium-Align successfully generated accurate keypoints for image registration.
- Automated alignment using Xenium-Align is feasible for spatial transcriptomics studies.
- The method was validated on diverse healthy and diseased tissue samples.
Conclusions:
- Xenium-Align offers an automated solution for keypoint generation in Xenium data analysis.
- This method facilitates efficient image alignment, improving cross-referencing of sequencing and histology data.
- Future work will focus on optimizing runtime efficiency and user-friendliness.
