Optimizing Your AI Strategy to Develop and Deploy Novel Deep Learning Models in the Cloud for Medical Image Analysis
, M.Sc. ETH Zürich, Product Owner and Data Engineering LOOP Zurich, University Hospital Balgrist
, Product Manager, Azure ML at Microsoft, Microsoft
With the inflection point of AI, medical operations are facing the paradigm shift of digitalization. Medical imaging is a key area for developing high value-added deep learning (DL) models that streamline and accelerate the process of image segmentation and classification, which is a major time-consuming task for physicians. Balgrist University Hospital is using tools and frameworks included with NVIDIA AI Enterprise, such as MONAI, supported by Microsoft's Azure AI Machine Learning Studio infrastructure. Learn how Balgrist University Hospital is leveraging NVIDIA and Microsoft solutions for developing and deploying DL models for semantic segmentation of musculoskeletal images, which are fundamental for computer-aided 3D surgical planning and corresponding intraoperative navigation, supported by augmented reality and/or robotic devices. Also hear how NVIDIA AI Enterprise integrated with Azure Machine Learning provides an enterprise-ready, secure, end-to-end MLOps platform that enables enterprises to streamline their ML life cycle.