Journal article
Virtual alignment of pathology image series for multi-gigapixel whole slide images
- Abstract:
- Interest in spatial omics is on the rise, but generation of highly multiplexed images remains challenging, due to cost, expertise, methodical constraints, and access to technology. An alternative approach is to register collections of whole slide images (WSI), generating spatially aligned datasets. WSI registration is a two-part problem, the first being the alignment itself and the second the application of transformations to huge multi-gigapixel images. To address both challenges, we developed Virtual Alignment of pathoLogy Image Series (VALIS), software which enables generation of highly multiplexed images by aligning any number of brightfield and/or immunofluorescent WSI, the results of which can be saved in the ome.tiff format. Benchmarking using publicly available datasets indicates VALIS provides state-of-the-art accuracy in WSI registration and 3D reconstruction. Leveraging existing open-source software tools, VALIS is written in Python, providing a free, fast, scalable, robust, and easy-to-use pipeline for registering multi-gigapixel WSI, facilitating downstream spatial analyses.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Supplementary materials, pdf, 1.5MB, Terms of use)
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(Preview, Version of record, pdf, 9.0MB, Terms of use)
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- Publisher copy:
- 10.1038/s41467-023-40218-9
Authors
+ National Cancer Institute
More from this funder
- Funder identifier:
- https://ror.org/02t771148
- Grant:
- U01CA232382
- Publisher:
- Nature Research
- Journal:
- Nature Communications More from this journal
- Volume:
- 14
- Issue:
- 1
- Article number:
- 4502
- Place of publication:
- England
- Publication date:
- 2023-07-26
- Acceptance date:
- 2023-07-13
- DOI:
- EISSN:
-
2041-1723
- Pmid:
-
37495577
- Language:
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English
- Pubs id:
-
1499645
- Local pid:
-
pubs:1499645
- Deposit date:
-
2025-04-07
- ARK identifier:
Terms of use
- Copyright holder:
- Gatenbee et al.
- Copyright date:
- 2023
- Rights statement:
- © The Author(s) 2023. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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