awesome-pathology
github.com/open-pathology/awesome-pathology ↗Awesome List of Digital and Computational Pathology Resources
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me challenges resources from awesome-pathology"
Installation instructions →What's inside
Data
- ACDCChallenges
Automatic Cancer Detection and Classification of lung histopathology.
- ACROBATChallenges
AutomatiC Registration Of Breast cAncer Tissue.
- ADPReferences
Atlas of digital pathology for deep learning.
- ANHIRChallenges
Automatic Non-rigid Histological Image Registration.
- ARCHDatasets
Multiple instance captioning.
- BACHChallenges
BreAst Cancer Histology images.
Software
- ACMILModel
WSI classification.
- Aperio ImageScopeViewer (Free)
Freely downloadable software for viewing WSIs. Windows only.
- ASAPViewer
Desktop application for visualizing, annotating and automatically analyzing WSIs.
- BEPHModel
BEiT-based model pre-training on WSIs.
- Bio-FormatsImage IO
Java software tool for reading and writing microscopy image using standardized, open formats.
- BiomedCLIPFoundation Model
Multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs.
Publications
- breen2024ovarianPapers
Histopathology foundation models enable accurate ovarian cancer subtype classification.
- chen2022selfPapers
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology.
- jahanifar2023domainRepositories
Awesome domain generalization for computational pathology.
- kang2022benchmarkingPapers
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets.
- matous2024latentPapers
Are the latent representations of foundation models for pathology invarient to rotation?
- stettler2022datasetsRepositories
Resources of histopathology datasets.
Showing a sample of 161 resources. View the full list on GitHub →