MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging. Its ambitions are:
developing a community of academic, industrial and clinical researchers collaborating on a common foundation;
creating state-of-the-art, end-to-end training workflows for healthcare imaging;
providing researchers with the optimized and standardized way to create and evaluate deep learning models.
Features
The codebase is currently under active development.
flexible pre-processing for multi-dimensional medical imaging data;
compositional & portable APIs for ease of integration in existing workflows;
domain-specific implementations for networks, losses, evaluation metrics and more;
customizable design for varying user expertise;
multi-GPU data parallelism support.