PatternExtract: A facile, scalable pipeline for point pattern generation from spatial imaging data Article Swipe
Shruti Sridhar
,
Gayatri Kumar
,
Siddham Jasoria
,
Ziwei Meng
,
Patrick Jaynes
,
Vaibhav Rajan
,
David W. Scott
,
Claudio Tripodo
,
Kasthuri Kannan
,
Anand D. Jeyasekharan
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.06.25.661424
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1101/2025.06.25.661424
We present PatternExtract, an open-source pipeline that generates accurate spatial point patterns from RGB pathology images and cell coordinate data without relying on composite channels or proprietary software. Using a novel two-kernel tissue segmentation method combined with automated pixel classification in QuPath, PatternExtract precisely excludes tissue artifacts such as necrosis and blood vessels to define spatial windows. Optimized on 568 diffuse large B-cell lymphoma images and validated on an independent cohort, the pipeline enables robust spatial analyses.
Related Topics To Compare & Contrast
Concepts
Scalability
Pipeline (software)
Computer science
Point (geometry)
Database
Geometry
Operating system
Mathematics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2025.06.25.661424
- https://www.biorxiv.org/content/biorxiv/early/2025/06/28/2025.06.25.661424.full.pdf
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411759154
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