MONAI is the Medical Open Network for AI. Project MONAI was created with the goal of accelerating the pace of research and development by providing a common software foundation and a vibrant community for medical imaging deep learning.

MONAI is targeted for both the medical image computing (MIC) and the computer-assisted intervention (CAI) communities. It is an extension to PyTorch that includes specialized deep learning methods for diagnostic radiology, surgical planning, medical robotics, image-guided interventions, and nearly every other aspect of patient care.

MONAI provides a customizable interface to bring components to existing training pipelines or perform end-end training. Its goal is to increase efficiency and collaborations amongst researchers by providing domain-optimized foundational capabilities and standardization around algorithms’ benchmarking, evaluation, and reproducibility. These goals help improve reproducibility by not only being used as a framework for development but comparison, evaluation, and benchmarking by bringing together the community and organically converging on a standard set of best practices.