MONAI: A domain specialized, open source framework for accelerating Medical Imaging Research.
Description: It’s never been more important to put powerful AI tools in the hands of the world’s leading medical researchers – That is why Industry & Academic Research pioneers have joined forces to collectively build MONAI (Medical Open Network for AI). MONAI is a freely available, open source, community-supported, framework for deep learning in healthcare imaging guided by a network of AI Thought Leaders.
It provides domain-optimized best practices for developing healthcare imaging training workflows in a native PyTorch paradigm. In this talk/tutorial we will share the latest capabilities of MONAI from Foundational components that are domain specialized & GPU accelerated to more complex workflows & rich example walkthroughs. We will share best practices developed by MONAI and our collaborators for Medical Imaging Researchers enabling wide variety of use-cases to quickly get started on a common software foundation built with principles of reproducible research.
The talk would also include the latest & greatest state of the art research implementations from MICCAI’2020 submissions that would be available in MONAI. Our goal with MONAI is to collectively build a community of Medical Imaging Researchers providing a high quality, enterprise supported, common software foundation for collaborative research, thus accelerating the pace of innovation.
Join MONAI today on GitHub