To help place AI tools in the hands of the world’s leading medical researchers, NVIDIA, in collaboration with King’s College London, introduced MONAI, an open-source AI framework for healthcare research.
MONAI builds on best practices from existing tools, including NVIDIA Clara, NiftyNet, DLTK and DeepNeuro.
The framework is user-friendly, delivers reproducible results and is domain-optimized for the demands of healthcare data. It is also equipped to handle the unique formats, resolutions and specialized meta-information of medical images.
The first public release provides domain-specific data transforms, neural network architectures and evaluation methods to measure the quality of medical imaging models.
Available on GitHub, the open-source code is based on the Ignite and PyTorch deep learning frameworks, and brings together state-of-the-art libraries for data processing, 2D classification, 3D segmentation and more. Researchers can easily bring MONAI to their existing code, using the customizable design to integrate modular components into their AI workflows.
Read the full announcement, NVIDIA and King’s College London Announce MONAI Open Source AI Framework for Healthcare Research, on the NVIDIA Blog.