The MRI4All project aims to develop AI-based methods for optimizing MRI imaging while advancing data science competencies. Central to this effort is the enhancement of the manufacturer-independent MRI development platform gammaSTAR, alongside the creation of a domain-specific language (DSL) designed to streamline interaction with MRI systems.
Initially, the methodology will be tested using health data, with subsequent applications in material sciences, such as material testing. By utilizing AI-driven image optimization and system validation, the project imparts new data skills that will be incorporated into different learning formats.
Fraunhofer MEVIS contributes to the project with compact tabletop MRI systems, ideal for research and teaching purposes. MRI4All reduces barriers to accessing MRI technology and expands its applications in data-driven research and education. In the long term, the project aims to establish an innovation center for accessible MRI sequences in Bremen, ensuring the sustainable development and integration of the aquired data competencies.
Through these efforts, MRI4All strengthens DataNord’s profile areas of “Health Sciences” and “Material and Engineering Sciences”, fostering collaboration and advancing innovation across disciplines.
Team Members
DFKI: Prof. Dr. Rolf Drechsler, Prof. Dr. Christoph Lüth, Christina Plump
University of Bremen: Prof. Dr. Matthias Günther, Mareike Buck, Juela Cufe
Fraunhofer MEVIS: Dr. Daniel Christopher Hoinkiss
