Fraunhofer Institute for Digital Medicine MEVIS
Grand Challenge is a well-known platform for end-to-end development of machine learning solutions in biomedical imaging. The platform is open source, developed largely by the Diagnostic Image Analysis Group at the Radboud University Medical Center Nijmegen, and the main installation runs on AWS, with more than 100,000 registered users, several hundred registered challenges, and many ready-to-run AI algorithms.
On the one hand, the use of public cloud technologies facilitates the scalable public deployment, which allows many concurrent users to run algorithms on cloud machines on data uploaded into the platform. On the other hand, institutional regulations may not allow the use of the platform with local research datasets, e.g., if they must not be uploaded to commercial cloud platforms. Such issues motivate a more decentralized approach.
Fraunhofer MEVIS is addressing this problem by developing solutions that enable the secure and decentralized use of research data as part of the NFDI4Health project. A central measure is the provision of dedicated hardware for a local Grand Challenge node that interacts with the central Grand Challenge platform where it makes sense.