Pathology
The Pathology area is a web workspace for computational pathology and whole-slide imaging research. Upload tissue slides or region images; generate tile manifests for browser viewing; run tissue detection, cell segmentation, and spatial quantification; inspect overlays in the slide viewer; and track reproducible pipeline runs.
Start from a research scenario
Guided workflows map common questions to data requirements, analysis steps, and documentation — pick the scenario closest to your study.
Slide quantification
Research question: What is the tissue composition of this slide, how many cells are detected, and what spatial metrics characterize the tissue architecture?
Run the full computational pathology pipeline on a tissue slide — tile generation, tissue detection, cell segmentation, and spatial quantification with interactive viewer review.
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TME infiltration
Research question: How infiltrated is the tissue, what is the spatial organization of detected cells, and does the infiltration pattern suggest immune-desert, excluded, or inflamed phenotypes at the tissue level?
Quantify tumor microenvironment architecture — cell density patterns, immune infiltration phenotype, and spatial proximity metrics from segmented tissue slides.
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Annotated compartments
Research question: What are the cell counts, densities, and spatial statistics within each labeled tissue compartment rather than across the whole slide?
Quantify cell density and spatial metrics within pathologist-defined regions — tumor, stroma, necrosis, or lymphoid compartments imported from GeoJSON or QuPath exports.
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Multiplex IF phenotyping
Research question: Which marker-positive cell populations are present in this tissue, how do markers co-occur on the same cells, and how does phenotype composition vary across tissue regions?
Turn a multi-channel immunofluorescence image and a completed cell segmentation into per-cell marker positivity, phenotype calls, and region-level composition — beyond what H&E morphology alone can resolve.
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TMA analysis
Research question: Where is each tissue core on this TMA slide, what row/column position does it occupy, and are any expected cores missing or lost?
Break a tissue microarray (TMA) slide into its individual cores — detected, laid out on a labeled grid, and flagged for missing positions — before running per-core quantification.
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Spatial omics context
Research question: Where do spatial gene expression signals originate relative to tissue structure, and how can morphology-guided regions connect molecular data to what pathologists see on the slide?
Ground spatial transcriptomics in tissue morphology — pathology provides the WSI tissue context layer that makes Visium, Xenium, and MERFISH results interpretable in histological space.
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Platform features
Everything available in the Pathology workspace today — pipelines, explorers, exports, and provenance.
- Study containers for whole-slide imaging and region-image projects
- Slide upload for TIFF, OME-TIFF, PNG, JPEG, and scanner-format files
- Multi-level tile generation with thumbnail and pyramid manifests for web viewing
- Tissue detection producing masks, region bounding boxes, and focus QC summaries
- Cell and nucleus segmentation with overlay PNG and structured cell tables
- Pluggable segmentation engines: watershed splitting of touching nuclei with split-count and boundary-quality QC
- Spatial quantification: cell density heatmaps across tissue regions
- Nearest-neighbor distance statistics between detected cells
- Infiltration phenotype scoring and region-level metric summaries
- CSV and JSON exports for downstream statistical analysis
- Interactive slide viewer with pan/zoom tile rendering, a minimap navigator, and synced side-by-side slide comparison
- Viewer layers for tissue mask, cell overlay, and density heatmaps
- GeoJSON and QuPath-compatible annotation import
- OME-TIFF export and QuPath-native GeoJSON round-trip (class + color) for QuPath/Fiji/OMERO interoperability
- Tissue microarray dearraying: detect cores into a labeled grid, flag missing cores, and a TMA map viewer with per-core tissue fraction
- Stain color deconvolution for H&E and IHC (H-DAB) with per-stain channels and DAB-positive area quantification
- Interactive annotation authoring: draw polygon/rectangle/point regions, classify (tumor/stroma/necrosis/…), move, delete, and export GeoJSON
- Trainable cell classifier: learn cell classes from annotation regions with cross-validated accuracy, per-class metrics, and feature importances
- Cell morphometrics (area, perimeter, circularity, eccentricity, solidity, axes) with an interactive measurement explorer: sortable tables, histograms, scatter plots, and CSV export
- Study-level pipeline run history with linked artifacts
- Cohort comparison of pathology biomarkers across sample groups
- Reproducible pipeline versioning recorded on every analysis run
- Async pathology job dispatch with queued, running, and complete states