Open-Source Network for AI Gaining Momentum

Duke AI Health in North Carolina recently hosted a presentation about MONAI by Stephen Aylward, Ph.D., chair of the MONAI advisory board, and the senior director of strategic initiatives for Kitware Inc., a company involved in the research and development of open-source software in the fields of computer vision, medical imaging, visualization, 3D data publishing, and technical software development. “Its goal is to accelerate the pace of research and development by providing a common software foundation and a vibrant community for medical image deep learning,” he said. MONAI Label is an intelligent image labeling and learning tool that uses AI assistance to reduce the time and effort of annotating new datasets. By utilizing user interactions, MONAI Label trains an AI model for a specific task and continuously learns and updates that model as it receives additional annotated images. MONAI Core is the flagship library of Project MONAI and provides domain-specific capabilities for training AI models for healthcare imaging. Other new components include a MONAI Model Zoo and Federated Learning. As the MONAI website notes, federated learning is emerging as a promising approach for training AI models without requiring sites to share data, which is important in medical use cases, since there are privacy and regulatory restrictions to sharing data. A MONAI “Deploy” work group is seeking to define how to close the existing gap from research and development to clinical production environments by bringing AI models into medical applications and clinical workflows with the end goal of helping improve patient care.