Fraunhofer Institute for Digital Medicine MEVIS

Fraunhofer MEVIS is a research institute dedicated to improving health care through the development and marketing of solutions for digital medicine. With a focus on early detection, diagnosis, and therapy of diseases such as cancer and diseases of the circulatory system, brain, breast, liver, and lung, the institute is committed to detecting diseases earlier and more accurately, tailoring treatments to each individual, and making therapeutic success more measurable. 

To achieve its mission, Fraunhofer MEVIS works closely with medical technology and pharmaceutical companies, providing solutions for the entire development chain, from applied research to certified medical products. The institute also develops software systems for industrial partners to perform image-based studies to determine the effectiveness of medicine and contrast agents. 

To ensure its work is relevant, Fraunhofer MEVIS collaborates closely with clinical and industrial partners to select research topics based on their expected impact on medical care and to translate its R&D results into viable innovations. The institute leverages its expertise in medical computing, including image acquisition and reconstruction, image processing and analysis, mathematical modeling and simulation, machine learning, and human-computer interaction and user experience engineering, to improve the accuracy, safety, and efficiency of diagnostic and therapeutic procedures. 

With its focus on rapid prototyping of software applications, modular software development, and efficient ISO-certified quality assurance, Fraunhofer MEVIS positions itself as a leading partner for research and development in the area of computer-assisted medicine, as well as for the translation of research results into medical products.

Role in the project

MEVIS is most prominently involved in the creation of high-quality software. This comprises the open source implementation of the decentralized swarm learning framework including the digital ledger technology to ensure safety and accountability, which is one of the major publishable outcomes of the project. To achieve this, MEVIS will ensure that from day one of the project all artifacts are created to conform to rigorous quality assurance guidelines. This extends to the processes and data prerequisites required for future certification of (continuously) trained models. In addition, MEVIS contributes in the creation of all software and models.


Volkmar Schulz

Volkmar Schulz is a professor at the University RWTH Aachen in Germany, where he serves as the head of the department of “Physics in Molecular Imaging Systems”. He has a background in Information Technology and holds a Dr.-Ing. degree in electrodynamics and integrated optics. After starting his industry career at Philips Research in Hamburg, he quickly rose to Principal Scientist for MRI-PET. In 2019, he joined Fraunhofer MEVIS as an expert in AI-based image reconstruction and founded the RWTH spin-off company Hyperion Hybrid Imaging Systems GmbH, of which he is currently CEO. Throughout his career, Professor Schulz has made significant contributions to the field of imaging technology, authoring over 200 publications and 70 patents. He has also been successful in coordinating several DFG, BMBF, and  EU FP7 and H2020 projects, such as HYPERImage, SUBPLIMA, Hypmed, HD-MetaPET.


Markus Wenzel

Markus Wenzel is a computer scientist, and at Fraunhofer MEVIS key scientist for Computational Breast Care and for Cognitive Computing. He leads the institute’s strategic efforts with regard to Clinical Decision Support systems. His clinical domain expertise regards image-based breast cancer care using machine learning and deep learning methods for detection, diagnosis, and decision making. He was and is involved in the creation and lead of several European breast cancer related projects. Besides his research, he teaches deep learning and image processing at Constructor University, Bremen, Germany; and for the Fraunhofer Academy in a Data Scientist Certificate program.