Evidence map›Paper›PMID 40643521›Full record

ArticleCells2025

Defining Keypoints to Align H&E Images and Xenium DAPI-Stained Images Automatically.

Yu Lin, Yan Wang, Juexin Wang, Mauminah Raina, Ricardo Melo Ferreira, Michael T Eadon, Yanchun Liang, Dong Xu

Abstract read
In one paragraph

Article in Cells, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Yu LinSchool of Artificial Intelligence, Jilin University, Changchun 130012, China.
Yan WangSchool of Artificial Intelligence, Jilin University, Changchun 130012, China.ORCID 0000-0002-4751-0708
Juexin WangDepartment of Biomedical Engineering and Informatics, Indiana University Indianapolis, Indianapolis, IN 46202, USA.ORCID 0000-0002-2260-4310
Mauminah RainaDepartment of Biomedical Engineering and Informatics, Indiana University Indianapolis, Indianapolis, IN 46202, USA.
Ricardo Melo FerreiraDepartment of Medicine, Indiana University Indianapolis, Indianapolis, IN 46202, USA.
Michael T EadonDepartment of Medicine, Indiana University Indianapolis, Indianapolis, IN 46202, USA.
Yanchun LiangKey Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China.ORCID 0000-0002-1147-3968
Dong XuDepartment of Electrical Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211, USA.ORCID 0000-0002-4809-0514

Funding

Development Project of Jilin Province of China No. 20220508125RCGuangdong Engineering Centre No. 2024GCZX001Guangdong Specialized Talent Training Program No. 2024001National Key R&D Program No. 2018YFC2001302National Natural Science Foundation of China 62372494
6 · The paper itself

Abstract

10X Xenium is an in situ spatial transcriptomics platform that enables single-cell and subcellular-level gene expression analysis. In Xenium data analysis, defining matched keypoints to align H&E and spatial transcriptomic images is critical for cross-referencing sequencing and histology. Currently, it is labor-intensive for domain experts to manually place keypoints to perform image registration in the Xenium Explorer software. We present Xenium-Align, a keypoint identification method that automatically generates keypoint files for image registration in Xenium Explorer. We validated our proposed method on 14 human kidney samples and one human skin Xenium sample representing healthy and diseased states, with expert manually marked results. These results show that Xenium-Align could generate accurate keypoints for automatically implementing image alignment in the Xenium Explorer software for spatial transcriptomics studies. Our future research aims to optimize the method's runtime efficiency and usability for image alignment applications.

Indexed as

Image Processing, Computer-AssistedStaining and LabelingGene Expression ProfilingHumansKidneySoftwareTranscriptomegraph matchingH&E imageimage alignmentnucleus segmentationspatial transcriptomicsXenium technology

Identifiers

PMID40643521
PMCPMC12248767

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.