Project development in AI in healthcare domain can be exhausting. Because computer vision and image processing methods in healthcare are quite different from regular methods. Basically, evaluation methods and KPIs are different in medical models from others. Additionally, there are many imaging modalities and every modality has its own data and labelling structure. We need healthcare-specific solutions to standardize methods and reproduce research results.
Table of Contents
What is MONAI?
Project MONAI is started by NVIDIA and King’s College London and MONAI is developed by Project MONAI. Its name comes from initials of Medical Open Network for Artificial Intelligence and it is a Python framework for healthcare imaging. It provides healthcare domain-optimized features for developers. It brings PyTorch ecosystem to healthcare-specific applications because it is based on PyTorch. It is published open-source and distributed with Apache 2.0 licence.
MONAI solves many of our problems when we encounter developing AI models in healthcare. Shortly, it brings standardized, user friendly, reproducible and high quality code structure and it covers end-to-end workflow with labeling, training and deployment tools. You can visit MONAI Project web site from here.
How to Install MONAI?
MONAI has three components: MONAI Label, MONAI Core and MONAI Deploy. Every component should be installed separately. We can use pip to install each component.
pip install monai pip install monailabel pip install monai-deploy-app-sdk
That’s all! We’ve installed all components. Now, we can start our projects about AI in medicine.