STAMP
importedsoftware/stamp
Solid Tumor Associative Modeling in Pathology
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- KatherLab
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/KatherLab/STAMP
- Documentation
- unknown
- Tags
- agents · bioimage-analysis · bioinformatics · deep-learning · digital-pathology · heatmaps-visualization-tool · histopathology · mcp
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- cytominebioimage-analysis · digital-pathology
A web platform for collaborative analysis of very large bio-medical images
- qupathbioimage-analysis · digital-pathology
QuPath - Open-source bioimage analysis for research
- aestetikbioinformatics · digital-pathology · histopathology
AESTETIK: Convolutional autoencoder for learning spot representations from spatial transcriptomics and morphology data
- DeepSpotbioinformatics · digital-pathology · histopathology
DeepSpot: Deep learning model for predicting spatial transcriptomics from H&E histopathology images. Supports spot-level (Visium) and single-cell (Xenium) resolution.
- pyclesperanto_prototypebioimage-analysis
GPU-accelerated bio-image analysis focusing on 3D+t microscopy image data
- ACMILdigital-pathology · histopathology
Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)
- api.github.com/repos/KatherLab/STAMPretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-07-07, 125 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/4.json→ .entries["stamp"]
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