Image analysis for radiology

Since VRVis was established, we have been developing machine learning and deep learning methods to support radiologists in many diagnostic tasks in routine clinical practice. VRVis solutions in radiology have been published in high-impact journals and have been patented as well as being successfully integrated into our customers’ products. They are already accelerating radiology workflows in hospitals worldwide.


Virtual intervention planning and support

Virtual training, intervention and planning tools have long been an important work principle in surgery. In close cooperation with surgeons, VRVis has created both preoperative planning tools and solutions for intraoperative support for interventions, for example in neurosurgery, orthopaedics and cardiac surgery. Depending on the application, we combine our extensive expertise in real-time visualisation of 3D image data, automatic image analysis, human-computer interaction, and AR and VR experience in tailor-made solutions.

Many of our solutions have been used in clinical situations, won several awards and been published in high-impact journals.

Selection of publications

Data science and visual analytics for healthcare and patient data

Analysing large volumes of data and selected patient cohorts has long been one of the main approaches in research, for example to investigate basic epidemiological processes, and develop personalised prediction models and treatment strategies for patients. In researching rare diseases, when patient numbers are insufficient, it is less the volume and more the combination of complex heterogeneous data sets that plays a role in recording as complete an image as possible of the disease and its molecular, demographic and clinical background. VRVis has already implemented several projects which support medical professionals and life scientists in, for example, research into rare types of cancer and in stable statistical analysis of patient cohorts.



Successful radiotherapy and precise radiation planning are closely linked. At the heart of both is patient safety, which is ensured by the most exact targeting of the tumour so as to prevent unnecessary radiation and damage to healthy tissue. Within the framework of the interdisciplinary EU project SUMMER, new approaches to data visualisation have been developed by VRVis. Through the combined visualisation of different imaging methods and the possibility of interacting with the data, the medical professionals from oncology, radiology and physics are able to better identify the biological target volume of a tumour, therefore allowing them to plan more tailored radiotherapy. SUMMER was awarded a European prize.

Selection of publications