This curated list of useful resources is supported by:
- 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.
- 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.
- 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.
- svg2svs - Generate checkerboard and build multi-layer pyramidal SVS files from SVG images.
- tifffile - Read and write TIFF-like files using in bioimaging.
- WholeSlideData - Batch iterator that enables fast, efficient and easy patch sampling.
- 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.
- PathML - Tools for computational pathology.
- Slideflow - Python package that provides a unified API for building and testing deep learning models for histopathology.
- 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.
- CONCH - Vision-language foundation model for computational pathology.
- 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.
- HIPT - Scaling vision transformers to gigapixel images via hierarchical self-supervised learning.
- 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.
- LongViT - Vision Transformer that can process gigapixel images in an end-to-end manner.
- MCAT - Multimodal co-attention transformer for survival prediction in gigapixel WSIs.
- 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.
- 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.
- 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.
- 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.
- Digital Slide Archive - Provides the ability to store, manage, visualize and annotate large imaging datasets.
- ASAP - Desktop application for visualizing, annotating and automatically analyzing WSIs.
- Cytomine - Collaborative analysis of 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.
- QuPath - Java application that enables researchers and pathologists to visualize, analyze and annotate WSIs.
- Aperio ImageScope - Freely downloadable software for viewing WSIs. Windows only.
- 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.
- Gleason 2019 - Automatic Gleason grading of prostate cancer in digital histopathology.
- HER2 Scoring Contest - Automated HER2 scoring algorithms in WSI of breast cancer tissues.
- HEROHE - Predicting HER2 status in breast cancer from H&E.
- 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.
- 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.
- CryoNuSeg - Nuclei segmentation of cryosectioned H&E-stained histological images.
- H2T - Handcrafted Histological Transformer for unsupervised representation of WSIs.
- LC25000 - Lung and colon cancer histopathological image dataset.
- LyNSeC - Lymphoma nuclear segmentation and classification dataset.
- MHIST - Minimalist histopathology image analysis dataset.
- NuInsSeg - A fully annotated dataset for nuclei instance segmentation in H&E-stained histological images.
- 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.
- PCAM - PatchCamelyon provides a new benchmark for machine learning models akin to CIFAR-10 and MNIST.
- TCGA - The Cancer Genome Atlas is a landmark cancer genomics program that molecularly characterized over 20,000 primary cancer and matched normal samples spanning 33 cancer types.
- UNITOPATHO - A labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading.
- UNMaSk - Unmasking the immune microecology of ductal carcinoma in situ.
- ADP - Atlas of digital pathology for deep learning.
- Cytomine Collection - Open access to high quality WSI in several formats.
- DICOM WSI Standard - DICOM WSI document.
- Jerad Gardner, MD - Popular YouTube channel for educational videos by a pathologist.
- WebPathology - Visual survey of surgical pathology.
- chen2022self - Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology.
- kang2022benchmarking - Benchmarking Self-Supervised Learning on Diverse Pathology Datasets.
- wolflein2023good - A Good Feature Extractor Is All You Need for Weakly Supervised Pathology Slide Classification.
- vaidya2024demographic - Demographic bias in misdiagnosis by computational pathology models.