The first time I touched MONAI is from a challenge: COVID-19 Lung CT Lesion Segmentation Challenge - 2020. The official originizer provided a banchmark implemented by MONAI.
I found MONAI is very helpful and have been using it untill now.
What is MONAI?
MONAI is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.
Features
- 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.
Installation
To install the current release, you can simply run:
pip install monaiPlease refer to the installation guide for other installation options.
Getting Started
MedNIST demo and MONAI for PyTorch Users are available on Colab.
Examples and notebook tutorials are located at Project-MONAI/tutorials.
Technical documentation is available at docs.monai.io.
Model Zoo
The MONAI Model Zoo is a place for researchers and data scientists to share the latest and great models from the community. Utilizing the MONAI Bundle format makes it easy to get started building workflows with MONAI.