MONAI

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.

pip install monai

To install from the source code repository:

pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI

Alternatively, pre-built Docker image is available via DockerHub:

  # with docker v19.03+
  docker run --gpus all --rm -ti --ipc=host projectmonai/monai:latest

Tutorials & examples are located at monai/examples.

Technical documentation is available via Read the Docs.

For guidance on making a contribution to MONAI, see the contributing guidelines.