whole-slide-imaging

Open source tools for computational pathology - Nature BME

QuPath - Open-source bioimage analysis for research

Cancer metastasis detection with neural conditional random field (NCRF)

Program for the analysis and visualization of whole-slide images in digital pathology

Read and write TIFF files.

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

C library for reading virtual slide images

DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image

Bio-Formats is a Java library for reading and writing data in life sciences image file formats. It is developed by the Open Microscopy Environment. Bio-Formats is released under the GNU General Public License (GPL); commercial licenses are available from Glencoe Software.

Powerful, open-source AI tools for digital pathology.

Digital pathology image viewer with support for human/machine generated annotations and markups.

Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]

Code for paper: DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification [ECCV 2024]

Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024

a browser-based DICOM viewer

Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "

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

Solid Tumor Associative Modeling in Pathology

A Python module that produces image patches and annotation masks from whole slide images for deep learning in digital pathology.

🔥 🚀 Blazingly fast pipeline for patch-based classification in whole slide images