HEST: Bringing Spatial Transcriptomics and Histopathology together

Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data

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 🚀

This repo includes ChatGPT prompt curation to use ChatGPT better.

Transparent and reproducible medical image processing pipelines in Python.

Home for the unified VICTRE pipeline for in silico breast imaging.

A curated list for awesome self-supervised learning for graphs.

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

Boiler plate training code, trying to modularize as much as possible

Papers about explainability of GNNs

AAAI 2020 - ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Collection of resources related with Graph Contrastive Learning.

Sedeen compatibility

Must-read papers on graph neural networks (GNN)

Hover-net for nuclei instance segmentation and classification

Official code for "Self-Supervised driven Consistency Training for Annotation Efficient Histopathology Image Analysis" Published in Medical Image Analysis (MedIA) Journal, Oct, 2021.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Computational Pathology Toolbox developed by TIA Centre, University of Warwick.

A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

Solutions to the HuBMAP - Hacking the Kidney challenge.

Code and GUI for Feature-driven Local Cell Graph (FLocK): New Computational Pathology based descriptors

A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.

A library of core radiation therapy modules for DICOM RT used by dicompyler