Spatial biology processing suite
The AstroPath Pipeline was developed to process whole slide multiplex immunofluorescence data from microscope to database at single cell resolution.
OME-Zarr whole-slide images to patch- and slide-level foundation-model embeddings - cloud-native, FAIR, model- and backend-agnostic.
An R package for modeling asymmetric spatial associations between cell types in tissue images using a multilevel Bayesian framework.
This is a pipeline for ingestion, cleaning, and spatial analysis of Akoya PCF images
Python package for converting multiplex immunofluorescence single-cell exports from QuPath into AnnData objects for spatial analysis.
Configurable fingerprint-based cell-type annotation for CODEX and QuPath tables
A reproducible framework for modeling spatial cell–cell interactions in the tumor microenvironment using multitype Gibbs point processes and multiplexed imaging data.
Neighborhood-aware signal reallocation and normalization for multiplex spatial proteomics
Beyond Segmentation Accuracy: an expert-curated MxIF cell-segmentation benchmark, one leave-slide-out protocol for twelve segmenters, and a four-level biological-fidelity evaluation (cells, phenotypes, neighborhoods, tumor-immune organization). NeurIPS 2026 ASCI workshop. Non-commercial license; please cite.
Python workflows for tile-based feature extraction, clustering, and visualization of multiplex whole-slide imaging data.
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