Study workflow
Pathology follows a left-to-right research flow. Tile generation is required before browser viewing and segmentation on large slides.
Create study → Upload slides → Generate tiles → Tissue detect → Segment cells → Spatial quantification → Cohort / Interpret
Dashboard — area home
The pathology dashboard (/areas/pathology/dashboard) shows recent studies and links to create a new study.
Readiness signal: at least one study with one uploaded slide and a completed tile or analysis run.
Study home — project overview
The study page (/areas/pathology/studies/{id}) is your project hub:
- Slide ingestion — upload form with modality and stain type selectors
- Slides grid — thumbnail cards linking to slide detail pages
- Run history — all pipeline runs for this study
Slide detail — analyze and inspect
Each slide opens at /areas/pathology/studies/{id}/slides/{slideId}:
- Slide viewer — pan/zoom with overlay layers
- Pipeline controls — tile, tissue detect, segment, spatial quantification, multiplex phenotyping, color deconvolution, object classifier training, OME-TIFF export, spatial alignment
- QC panels — tissue fraction, cell count, spatial metrics
- Cell table — detected objects with area and confidence
- Region metrics table — compartment-level density and cell statistics
See Slide viewer.
Analyze — study-wide launcher
The Analyze page (/areas/pathology/studies/{id}/analyze) lists every slide in the study with quick-launch buttons for tiling, analysis jobs, and spatial alignment, plus the cohort workspace.
Cohort — group comparison
The Cohort page (/areas/pathology/studies/{id}/cohort) covers:
- CSV sample import and per-slide sample/group/timepoint assignment
- A batch pipeline launcher across selected slides
- The group-comparison table (t-test/Mann-Whitney or ANOVA/Kruskal-Wallis, FDR-corrected)
Interpret — AI-assisted summaries
The Interpret page (/areas/pathology/studies/{id}/interpret) generates a grounded narrative from one or more completed runs, with cited metrics and a research-use disclaimer. It is not yet linked from the study navigation — open it directly at that URL.
Typical paths
| Study type | Path |
|---|---|
| Region image demo | Upload PNG → tiles → tissue detect → segment → quantify |
| WSI review | Upload SVS/OME-TIFF → tiles → tissue QC → segmentation at scale |
| TME quantification | Segment → spatial quantification → export region metrics CSV |
| Annotated regions | Import GeoJSON → tissue detect → quantify within labeled compartments |
Integration with Computational Biology
Spatial transcriptomics ingestion, deconvolution, and generic spatial statistics are owned by the Computational Biology area. Pathology contributes the WSI tissue context layer — morphology-guided region extraction and overlay alignment — without duplicating compbio spatial pipelines.
Future workflow (planned)
- Publication-ready report export (methods text, figure export, reproducibility manifest)
- Cellpose/StarDist deep-learning segmentation models
- Slide-level and region-level collaboration comments