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 180 complete days
33 repositories by Attention Score · May 9, 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.
Simultaneous Nuclear Instance Segmentation and Classification in H&E Histology Images.
Prov-GigaPath: A whole-slide foundation model for digital pathology from real-world data
Vision-Language Pathology Foundation Model - Nature Medicine
⚡High Performance DICOM Medical Image Parser in Go.
3D medical imaging reconstruction software
Fellow Oak DICOM for .NET, .NET Core, Universal Windows, Android, iOS, Mono and Unity
Library for multiscale visualization of high-resolution multiplexed bioimaging data on the web. Directly renders Zarr and OME-TIFF.
Clinical Histopathology Imaging Evaluation Foundation Model
Dicoogle - Open Source PACS
Tools for computational pathology
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".
A Python interface to access neuroanatomical atlases
Interoperable web-based DICOM slide microscopy viewer and annotation tool
PyTorch Connectomics: segmentation toolbox for EM connectomics
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.
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.
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
Automated 3D cell detection in very large images
[Deprecated] Use Cornerstone3D Instead https://cornerstonejs.org/
U-Net Brain Tumor Segmentation
Neural networks toolbox focused on medical image analysis
Image restoration for fluorescence microscopy
Azure friendly DICOMweb part 18 .NET server with qido-rs, wado-rs, stow-rs, wado-uri RESTful implementation
AI-based pathology predicts origins for cancers of unknown primary - Nature
A pure JavaScript medical research image viewer.