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Feather - Lightweight supervised slide foundation models (ICML 2025)
Standardized benchmark for computational pathology foundation models.
Toolkit for large-scale whole-slide image processing.
This is a repo for code for graph models for whole slide image classification.
Feature engineering for big data and quick inference
KatherLab / STAMP-Benchmark
Forked from KatherLab/STAMPSolid Tumor Associative Modeling in Pathology
PathDino - Rotation-Agnostic Image Representation Learning for Digital Pathology (CVPR 2024)
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to ex…
List of pathology feature extractors and foundation models
LaTeX class for an undergraduate 4th year project (4YP) report or a DPhil / PhD doctoral thesis for a student of the Department of Engineering Science at the University of Oxford
Official Inplementation of 《WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole Slide Images》(MICCAI 2024 Oral/ Best Paper Candidate)
This repository contains the official implementation of the research paper: "Towards Training Large-Scale Pathology Foundation Models: from TCGA to Hospital Scale"
This repository contains all code to support the paper: "Preprocessing Pathology Reports for Vision-Language Model Development".
Clinical Histopathology Imaging Evaluation Foundation Model
Code / solutions for Mathematics for Machine Learning (MML Book)
Evaluation framework for oncology foundation models (FMs)
This package provides tools for training supervised machine learning models for computational pathology tasks using tile-level embeddings.
Code associated to the publication: Scaling self-supervised learning for histopathology with masked image modeling, A. Filiot et al., MedRxiv (2023). We publicly release Phikon 🚀
Self-guided notebook tutorials to help get started with IDC