QuPath - Open-source bioimage analysis for research

A Python toolkit for pathology image analysis algorithms.

Powerful, open-source AI tools for digital pathology.

Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge on BreAst Cancer Histology images (BACH)

Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell

AI-based pathology predicts origins for cancers of unknown primary - Nature

HEST: Bringing Spatial Transcriptomics and Histopathology together - NeurIPS 2024

Axon/Myelin segmentation using Deep Learning

The official deployment of the Digital Slide Archive and HistomicsTK.

Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering

Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024

A python package which aligns histology to the Allen Brain Atlas and Waxholm rat atlas using deep learning.

Open Scripts and pipelines from the Multimodal Imaging and Connectome Analysis Lab at the Montreal Neurological Institute

A pipeline to segment tissue from the background in histological images

A Girder plugin for pathology image annotations and analysis.

RandStainNA: Simple and efficient augmentations for histology [MICCAI 2022]

SIMPLI is a highly configurable pipeline for the analysis of multiplexed imaging data.

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'.

Dataset: landmarks for registration of histology images

The repository contains a simple pipeline for training Nuclei Segmentation Datasets of Histopathology Images.