1.Project-MONAI / MONAI
AI Toolkit for Healthcare Imaging
- healthcare-imaging
- deep-learning
- medical-image-computing
- medical-image-processing
- pytorch
- python3
- +1 more
Ranked by Attention Score: stars gained over the last 90 complete days
39 repositories by Attention Score · Aug 7, 2026 – Nov 4, 2026 (UTC)
AI Toolkit for Healthcare Imaging
Multi-platform, free open source software for visualization and image computing.
OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages
Pathology Foundation Model - Nature Medicine
TorchXRayVision: A library of chest X-ray datasets and models. Classifiers, segmentation, and autoencoders.
⚡High Performance DICOM Medical Image Parser in Go.
Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
Vision-Language Pathology Foundation Model - Nature Medicine
Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data
Library for multiscale visualization of high-resolution multiplexed bioimaging data on the web. Directly renders Zarr and OME-TIFF.
3D medical imaging reconstruction software
Fellow Oak DICOM for .NET, .NET Core, Universal Windows, Android, iOS, Mono and Unity
Dicoogle - Open Source PACS
Tools for computational pathology
Interoperable web-based DICOM slide microscopy viewer and annotation tool
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
A Python interface to access neuroanatomical atlases
Clinical Histopathology Imaging Evaluation Foundation Model
A foundation model-driven whole slide image-scale cell phenotyping method with QuPath integration Resources
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
PyTorch Connectomics: segmentation toolbox for EM connectomics
U-Net Brain Tumor Segmentation
Neural networks toolbox focused on medical image analysis
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Automated 3D cell detection in very large images
Automated 3D brain registration with support for multiple species and atlases.
ENIGMA HALFpipe is a user-friendly software that facilitates reproducible analysis of fMRI data
Axon/Myelin segmentation using Deep Learning
Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
AI-based pathology predicts origins for cancers of unknown primary - Nature
[Deprecated] Use Cornerstone3D Instead https://cornerstonejs.org/
Azure friendly DICOMweb part 18 .NET server with qido-rs, wado-rs, stow-rs, wado-uri RESTful implementation
Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"
⚡ Open-source software for deep learning-based digital pathology
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.