AG Virtual and Augmented Reality for Biomedical Computer Vision
Visual biomedical data has become a key feature for diagnostic, therapeutic and education purposes in modern medicine. State-of-the-art computer vision systems process and analyse this data to extract valuable information and to provide appropriate visualisation strategies. In this context, Virtual Reality (VR) and Augmented Reality (AR) devices have become particularly important since they offer immersive data representations and advanced interaction metaphors. Such techniques are well known for entertainment and gaming applications as well as industrial construction planning. Its applicability for daily clinical practice and biomedical image understanding is however yet in its infancy. Therefore, we aim to study and implement innovative VR and AR strategies for novel biomedical computer vision applications. This interdisciplinary research requires a close collaboration between medical and computer sciences in order to unleash the tremendous potential of VR and AR systems for clinical purposes.
Goals
- To determine the efficient usage of VR and AR devices for biomedical and clinical purposes
- The development of novel computer vision and machine learning algorithms to assess complex and high-dimensional medical image data
- The identification of innovative use-cases to apply VR and AR in diagnostic and therapeutic purposes
- To facilitate and support the usage of VR and AR system in medical education
- Our ultimate goal is to bridge the gap between rapidly emerging new vision technologies and their applicability for biomedical practice and research.
How to participate
If you are interested in a collaboration (e.g. clinical study, medical thesis, bachelor or master thesis) in this new and fast expanding field of medicine and computer science, please do not hesitate to contact us!
Contact

Prof. Dr. med. Markus Holling, MHBA
Professor for Neurosurgery
Consultant Neurosurgeon
Department of Neurosurgery, University Hospital Münster
Kontakt

Univ.-Prof. Dr. rer. nat. Benjamin Risse
Professorship for practical computer science
Computer Science Department
Computer Vision and Machine Learning Systems Group, University Münster
Kontakt
Further collaborators
Dr. Dimitar Valkov
Post-Doctoral Researcher
DFKI GmbH
Saarland Informatics Campus
Affiliate Researcher in the Computer Vision and Machine Learning Systems Group, Faculty of Mathematics and Computer Science, University Münster, Germany
Pascal Kockwelp
Research fellow
Master of Science
Faculty of Mathematics and Computer Science, University Münster, Germany
Klinik für Neurochirurgie
Albert-Schweitzer-Campus 1
Gebäude A1
48149 Münster