PyHIST

A Python toolkit for pathology image analysis algorithms.

Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)

Stain normalization tools for histological analysis and computational pathology

List of pathology feature extractors and foundation models

This is the official repository for our CVPR 2023 paper 'Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification'.

The official implementation of GPFM

MICCAI2022: Multiple Instance Learning with Mixed Supervision in Gleason Grading.

Code for the im4MEC model described in the paper 'Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts'.

[ICLR 2025] Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathology

Graph + Image Bimodal Deep Learning for Histology Image Classification