MICCAI 2022 Daily – Wednesday

30 DAILY MICCAI Wednesday Developing for the Medical AI Project Lifecycle An exciting journey started three years ago when NVIDIA and King's College London came together during MICCAI 2019 and formed Project MONAI as an initiative to develop a standardized, user-friendly, and open-source platform for Deep Learning in Medical Imaging . Soon after that, they established the MONAI Advisory Board and Working Groups with representatives from Stanford University, National Cancer Institute, DKFZ, TUM, Chinese Academy of Sciences, University of Warwick, Northwestern University, Kitware, and Mayo Clinic. Throughout this journey, MONAI has deepened its offering in radiology, expanded to pathology, and most recently, included support for streaming modalities starting with endoscopy. Now three years later, MONAI has over 600,000 downloads. It is used in over 450 GitHub projects, has been cited in over 150 published papers, and academic and industry leaders are using MONAI in their research and clinical workflows. We ’ re excited to announce that MONAI is continuing to expand open- source healthcare AI innovation with v1.0. With a focus on providing a robust API that is designed for backward compatibility, this release ensures that you can integrate MONAI into your projects today and benefit from the stability of an industry-leading framework into the future. Let's look at the features included in the MONAI Core v1.0, MONAI Label v0.5 releases, and a new initiative called the MONAI Model Zoo. Michael Zephyr is a Developer Evangelist for Healthcare at NVIDIA and one of the Group Leads for the MONAI Adoption and Outreach Working Group. Stephen Aylward is the Senior Director of Strategic Initiatives at Kitware. He is also a MICCAI Fellow and an adjunct professor of Computer Science at the University of North Carolina.