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awesome-pathology

Awesome List of Digital and Computational Pathology Resources
https://github.com/open-pathology/awesome-pathology

Last synced: 1 day ago
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  • Software

    • Foundation Model

      • Path Foundation - Embedding model for efficiently building AI for histopathology applications.
      • Virchow - Self-supervised vision transformer pretrained using 1.5M WSIs.
      • H-optimus - Foundation model for histology.
      • CONCH - Vision-language foundation model for computational pathology.
      • Hibou - A family of foundational vision transformers for pathology.
      • HIPT - Scaling vision transformers to gigapixel images via hierarchical self-supervised learning.
      • Phikon - Scaling self-supervised learning for histopathology with masked image modeling.
      • Prov-GigaPath - A whole-slide foundation model for digital pathology from real-world data.
      • ROAM - A transformer-based weakly supervised computational pathology method for clinical-grade diagnosis and molecular state revelation of gliomas.
      • TransPath - Transformer-based unsupervised contrastive learning for histopathological image classification.
      • UNI - General-purpose foundation model for computational pathology.
      • VIM4Path - Self-supervised vision mamba for WSIs.
      • PathoDuet - Foundation models for pathological slide analysis of H&E and IHC stains.
      • TITAN - Multimodal whole slide foundation model for pathology.
      • PathDino - Rotation-agnostic image representation learning for digital pathology.

    • Viewer (Free)

      • PathPresenter - A complete enterprise workflow platform built by pathologists.
      • Aperio ImageScope - Freely downloadable software for viewing WSIs. Windows only.

    • Image IO

      • libvips - A fast image processing library with low memory needs.
      • OpenSlide - Provides a simple C interface with Python bindings to read WSIs in multiple formats.
      • Bio-Formats - Java software tool for reading and writing microscopy image using standardized, open formats.
      • compay-syntax - Tissue mask and tiling pipeline.
      • cuCIM - NVIDIA's accelerated computer vision and image processing software library for multidimensional images.
      • svg2svs - Generate checkerboard and build multi-layer pyramidal SVS files from SVG images.
      • WholeSlideData - Batch iterator that enables fast, efficient and easy patch sampling.

    • Machine Learning

      • Slideflow - Python package that provides a unified API for building and testing deep learning models for histopathology.
      • DLUP - Deep learning utilities for pathology.
      • eva - Evaluation framework for oncology foundation models.
      • histocartography - Library designed to facilitate the development of graph-based computational pathology pipelines.
      • nuclei.io - Human-in-the-loop active learning framework for pathology image analysis.
      • PathML - Tools for computational pathology.

    • Model

      • LongViT - Vision Transformer that can process gigapixel images in an end-to-end manner.
      • ACMIL - WSI classification.
      • BEPH - BEiT-based model pre-training on WSIs.
      • Cell-DETR - Attention-based transformers for instance segmentation of cells in microstructures.
      • CellViT - Vision transformers for precise cell segmentation and classification.
      • Cerberus - Multi-task learning enables simultaneous histology image segmentation and classification.
      • CLAM - Data-efficient and weakly supervised computational pathology on WSI.
      • DeepLIIF - Deep-learning inferred multiplex immunofluorescence for immunohistochemical image quantification.
      • DiffInfinite - Large mask-image synthesis via parallel random patch diffusion in histopathology.
      • DMMN - Deep Multi-Magnification Network for multi-class tissue segmentation of WSI.
      • DT-MIL - Deformable transformer for multi-instance learning on histopathological image.
      • FrOoDo - Framework for out of distribution detection.
      • HistoGPT - Generating highly accurate histopathology reports from whole slide images.
      • HistoSegNet - Semantic segmentation of histological tissue type in WSIs.
      • HoVer-Net - Simultaneous segmentation and classification of nuclei in multi-tissue histology images.
      • MCAT - Multimodal co-attention transformer for survival prediction in gigapixel WSIs.
      • MMP - Multimodal prototyping for cancer survival prediction.
      • MSINet - Deep learning model for the prediction of microsatellite instability in colorectal cancer.
      • PANTHER - Morphological prototyping for unsupervised slide representation learning in computational pathology.
      • Patch-GCN - WSI are 2D point clouds: Context-aware survival prediction using patch-based graph convolutional networks.
      • RSP - Self-supervised driven consistency training for annotation efficient histopathology image analysis.
      • SparseConvMIL - Sparse convolutional context-aware multiple instance learning for WSI classification.
      • StainGAN - Stain style transfer for digital histological images.
      • stainlib - Augmentation & normalization of H&E images.
      • StainTools - Tools for tissue image stain normalisation and augmentation.
      • StarDist - Object detection with star-convex shapes.
      • TANGLE - Transcriptomics-guided slide representation learning in computational pathology.
      • TCGA segmentation - Weakly supervised multiple instance learning histopathological tumor segmentation.
      • torchstain - Stain normalization transformations.
      • TransMIL - Transformer based correlated multiple instance learning for WSI classification.
      • fseg - Unsupervised semantic segmentation for pathology by factorizing foundation model features.
      • Snuffy - Efficient WSI classifier.

    • Viewer

      • Cytomine - Collaborative analysis of WSIs.
      • QuPath - Java application that enables researchers and pathologists to visualize, analyze and annotate WSIs.
      • Cytomine - Collaborative analysis of WSIs.
      • ASAP - Desktop application for visualizing, annotating and automatically analyzing WSIs.
      • DigiPathAI - Tool to visualize gigantic pathology images and use AI to segment cancer cells and present as an overlay.
      • HistomicsUI - Web interface to visualize WSI and manage annotations.
      • slim - Interoperable web-based slide microscopy viewer and annotation tool.
      • QuickAnnotator - Model assisted tool for rapid annotation of WSIs.

    • Image Analysis

      • HistomicsTK - Toolkit for the analysis of digital pathology images.
      • HistoQC - Quality control tools for digital pathology.
      • PathProfiler - Quality assessment of histopathology WSI cohorts.
      • PyHIST - Histological image segmentation tool.
      • pyslide - Digital pathology WSI analysis toolbox.
      • TIA Toolbox - Computational pathology toolbox that provides an end-to-end API for pathology image analysis.

    • Platform

      • Digital Slide Archive - Provides the ability to store, manage, visualize and annotate large imaging datasets.

    • Assistant

  • Data

    • Challenges

      • LEOPARD - LEarning biOchemical Prostate cAncer Recurrence from histopathology sliDes.
      • KPIs - Kidney Pathology Image segmentation.
      • LYSTO - LYmphocytes aSsessment hackathOn in immunohistochemically stained tissue sections.
      • LYON19 - LYmphocyte detectiON in IHC stained specimens.
      • MIDOG 2021 - MItosis DOmain Generalization on tissue preparation and image acquisition.
      • MIDOG 2022 - MItosis DOmain Generalization on tissue types.
      • MITOS-ATYPIA-14 - Detection of mitosis and evaluation of nuclear atypia score.
      • MoNuSAC - Multi-Organ NUclei Segmentation And Classification.
      • MoNuSeg - Multi-Organ NUclei Segmentation.
      • PAIP2019 - Liver cancer segmentation.
      • PAIP2020 - Classification and segmentation of microsatellite instability (MSI) in colorectal cancer.
      • PAIP2021 - Perineural invasion in multiple organ cancer.
      • PAIP2023 - Tumor cellularity prediction in pancreatic cancer and colon cancer.
      • PANDA - Prostate cANcer graDe Assessment.
      • SegPC - Segmentation of multiple myeloma in Plasma Cells.
      • TIGER - Fully automated assessment of tumor-infiltrating lymphocytes (TILs) in H&E breast cancer slides.
      • TUPAC16 - TUmor Proliferation Assessment.
      • WSSS4LUAD - Weakly-supervised tissue semantic segmentation for lung adenocarcinoma.
      • ACDC - Automatic Cancer Detection and Classification of lung histopathology.
      • ACROBAT - AutomatiC Registration Of Breast cAncer Tissue.
      • ANHIR - Automatic Non-rigid Histological Image Registration.
      • BACH - BreAst Cancer Histology images.
      • BCI - Breast Cancer Immunohistochemical image generation.
      • BreastPathQ - Quantitative biomarkers for the determination of cancer cellularity.
      • CAMELYON16 - Cancer metastasis detection in lymph node.
      • CAMELYON17 - Building on CAMELYON16 by moving from slide level analysis to patient level analysis.
      • CellSeg - Cell segmentation in multi-modality high-resolution microscopy images.
      • CoNIC - Colon Nuclei Identification and Counting.
      • DigestPath 2019 - Digestive-system pathological detection and segmentation.
      • ENDO-AID - Endometrial carcinoma detection in pipelle biopsies.
      • HER2 Scoring Contest - Automated HER2 scoring algorithms in WSI of breast cancer tissues.
      • HEROHE - Predicting HER2 status in breast cancer from H&E.
      • HER2 Scoring Contest - Automated HER2 scoring algorithms in WSI of breast cancer tissues.
      • MONKEY - Machine-learning for Optimal detection of iNflammatory cells in the KidnEY.
      • Gleason 2019 - Automatic Gleason grading of prostate cancer in digital histopathology.

    • Datasets

      • ARCH - Multiple instance captioning.
      • BCNB - Early Breast Cancer Core-Needle Biopsy WSI dataset.
      • BCSS - Breast Cancer Semantic Segmentation.
      • BRACS - BReAst Carcinoma Subtyping.
      • CRC - 100,000 histological images of human colorectal cancer and healthy tissue.
      • MHIST - Minimalist histopathology image analysis dataset.
      • NuCLS - A scalable crowdsourcing approach & dataset for nucleus classification, localization and segmentation in breast cancer.
      • OCELOT - Overlapped cell on tissue dataset for histopathology.
      • PanNuke - Dataset for nuclei instance segmentation and classification.
      • CryoNuSeg - Nuclei segmentation of cryosectioned H&E-stained histological images.
      • H2T - Handcrafted Histological Transformer for unsupervised representation of WSIs.
      • HEST - Bringing spatial transcriptomics and histopathology together.
      • UNITOPATHO - A labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading.
      • UNMaSk - Unmasking the immune microecology of ductal carcinoma in situ.
      • PanNuke - Dataset for nuclei instance segmentation and classification.
      • LC25000 - Lung and colon cancer histopathological image dataset.
      • LyNSeC - Lymphoma nuclear segmentation and classification dataset.
      • NuInsSeg - A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.
      • PCAM - PatchCamelyon provides a new benchmark for machine learning models akin to CIFAR-10 and MNIST.
      • UNITOPATHO - A labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading.
      • UNMaSk - Unmasking the immune microecology of ductal carcinoma in situ.
      • HEST - Bringing spatial transcriptomics and histopathology together.
      • LC25000 - Lung and colon cancer histopathological image dataset.

    • References

  • Publications

    • Papers

      • kang2022benchmarking - Benchmarking Self-Supervised Learning on Diverse Pathology Datasets.
      • chen2022self - Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology.
      • wolflein2023good - A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.
      • vaidya2024demographic - Demographic bias in misdiagnosis by computational pathology models.
      • chen2022self - Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology.
      • wolflein2023good - A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.
Programming Languages
Python 43 Jupyter Notebook 17 JavaScript 4 C++ 2 HTML 1 MATLAB 1 TypeScript 1 Java 1
Categories
Software 78 Data 64 Publications 6
Sub Categories
Challenges 35 Model 32 Datasets 23 Foundation Model 15 Viewer 8 Image IO 7 Machine Learning 6 Image Analysis 6 Papers 6 References 6 Viewer (Free) 2 Assistant 1 Platform 1
Keywords
computational-pathology 23 pathology 16 deep-learning 16 histopathology 16 digital-pathology 12 python 12 whole-slide-imaging 9 pytorch 8 medical-imaging 7 machine-learning 6 mahmoodlab 6 wsi 6 histology 6 segmentation 5 weakly-supervised-learning 5 whole-slide-image 4 quantitative-pathology 4 self-supervised-learning 4 cell-segmentation 4 image-analysis 4 bioimage-informatics 4 computer-vision 3 tcga-data 3 image-segmentation 3 camelyon16 3 digital-slide-archive 3 pathology-image 3 microscopy 3 vision-transformer 2 unsupervised-learning 2 transfer-learning 2 pretrained-weights 2 multimodal 2 image-processing 2 nature-medicine 2 optimal-transport 2 foundation-model 2 multiple-instance-learning 2 spatial-transcriptomics 2 ai 2 bioimage-analysis 2 cancer 2 medical-image-processing 2 medical-image-analysis 2 openslide 2 stain-normalization 2 histopathology-images 2 svs 2 data-efficient 2 ai-ready 1