Imaging is one of the key data acquisition technologies in medicine and life sciences and an extremely fast evolving technology delivering increasingly detailed insights into structure and function of organisms. This rich source of information enables fundamental insights into biological processes, but also supports the ongoing efforts to realize personalized medicine. However, scientists and physicians are confronted with an ongoing explosion of imaging data that has to be processed, inspected, analyzed and correlated and the ability to efficiently get access to the core information encoded in this data decides on its final usefulness.
The Biomedical Image Informatics Group is an interdisciplinary team addressing the above challenge by providing novel visual computing solutions covering complete image based workflows in medicine and life science.
Recent solutions developed by the group cover high performance image analysis solutions for radiology, visualization solutions for intervention planning, radar image analysis for environmental studies and the development of complete IT infrastructures for management, analysis, visualization and data mining of large image data collections for neurosciences. The group is IT partner of the Austrian BioImaging/CMI that is providing access to high end imaging modalities and imaging services in Austria.
Scientific Director | Head of Biomedical Image Informatics Group, Biomedical Image Informatics
buehler(at)vrvis.at +43 1 908 98 92 401Behind our smart solutions and software are smart and driven people. Do you want to meet the team?
See all the patents by the Biomedical Image Informatics Group.
AGFA Healthcare, GE, BrainCon, Aquilab, Medtronics, Medical University Vienna, Leipzig University, Universitaetsklinikum Freiburg, Oncolopole Toulouse, Donau University Krems, Medical University of Graz
Boehringer Ingelheim, IMP - Institute of Molecular Pathology Vienna, CNRS - Tefor.net, HHMI, Baxter, University Konstanz, Austrian BioImaging/CMI, coopNatura,
TU Wien, Vienna University, RWTH Aachen, University Magdeburg, TU Delft
RHI Magnesita
The expertise of our Biomedical Image Informatics research group is in high demand – read all about it in various recent press articles or see dates for upcoming lectures:
"XAI – Vertrauenswürdige Künstliche Intelligenz: Das Denken der Neuronalen Netze verstehen lernen", in: APA Science, November 2022
"Wir beschleunigen Entscheidungen", in: APA Science, January 2021
"Wie der KI-Assistenzarzt entscheidet", in: Der Standard, November 2020
Due to climate change, extreme weather events are becoming more frequent and new pests are establishing in agriculture. Together with three project partners, VRVis is developing a digital imaging system for plants that combines information from magnetic resonance imaging and positron emission tomography and detects stress symptoms in plants at an early stage.
The aim of the application project IVC Multi is to research novel intelligent visual computing methods supporting decision-making in automotive industry, medicine, and life sciences based on ensembles of heterogeneous, multi-scale and/or multi-temporal data.
The aim of the project IVC Stream is to research novel visual computing solutions for simulation and measurement data.
This project aims at accelerating and automating image-based decision making with an application focus on medicine, recycling and quality assurance processes in manufacturing.
The strategic project of the area is the organizational and scientific hub for the realization of the area-wide intelligent visual computing approach for analytics and modelling based on ensembles of dense grid-based data, derived data, and digital embedding.
Within the project Larvalbrain 2.0, a dynamic multi-scale multi-level atlas and data collection of structural, molecular, physiological, and behavioral results of Drosophila melanogaster larvae will be established.
VRVis a founding member of the Austrian BioImaging/CMI, which is a professional consortium of multiple Austrian science institutions and the official Austrian Euro-BioImaging initiative.
COMULIS is an EU-funded COST Action that aims at fueling collaborations in the field of correlated multimodal imaging (CMI).
Understanding how the brain works is one of the biggest challenges addressed by neuroscientists today. Modern neuroscience research is extremely data-intensive and requires special software infrastructures to enable and accelerate the discovery of the complex interplay of genes, structure and function.
Visual computing for medicine: image processing solutions for new applications in radiology.
The long-term vision of this applied research project is to use available data resources to improve image-based diagnostics based on complex data in daily clinical routine.
The combination of "liquid biopsies", machine learning and data visualization aims to enable earlier and more accurate prediction of a relapse in children with cancer.
The strategic project forms the organizational and scientific hub for the realization of an area wide integrative visual computing approach. It covers joint strategic research and development on fundamental challenges in all application projects.
Complex simulation data is practically omnipresent today.
For centuries, neuroscientists have been mapping the brain. Until now, the step from simple maps to a generally accepted model has proved to be extremely difficult. In this project, a 4D atlas of the brain of the fruit fly larva is being built.
VRVis contributes data analytics and visualization tools tailored to support and accelerate research of the Haubensak Group at the Institute of Molecular Pathology Vienna.
Visual computing techniques for the automated detection of osteoporosis and osteoarthritis.
Software for the use of multi-modality images in external radiotherapy.
Next generation workflows for interactive knowledge generation from images and simulations.
The analysis, visualization and exploration of high-dimensional image spaces are the subject of the KAFus project.
To enable people to live an economically, ecologically and socially sustainable life, applications by VRVis contribute to 10 of the 17 Sustainable Development Goals (SDGs). Due to this, VRVis is now nominated for the Austrian SDG-Award.
Theresa Neubauer, a researcher in our Biomedical Image Informatics Group, received the 2022 OCG Promotion Award.
Researchers Theresa Neubauer and Silvana Zechmeister were each awarded a sponsorship prize from the Dr. Maria Schaumayer Stiftung for their diploma theses at VRVis.
New VRVis AI method that boosts confidence in computer-aided diagnosis receives the eAward 2021.
A team of VRVis and AGFA employees won the last AGFA Healthcare Ship-it Day of the year.
Monika Wißmann, FEMtech intern at VRVis, receives the "IEEE Women in Engineering Best Student Paper Award".
On March 3, 2020, Katja Bühler, head of our Biomedical Image Informatics Group, was awarded with the renowned TU Women's Prize.
Katja Bühler is nominated for the Women in Tech Award 2019 of the Federal Ministry for Digital and Economic Affairs and the Futurezone!
Florian Ganglberger's short paper received an Honorable Mention at the EG VCBM 2019.
Johanna Schmidt and Sophia Ulonska are nominated for the Hedy Lamarr Award by the city of Vienna.
During the 40th anniversary celebration of the Austrian Computer Society (OCG) on June 9, 2015, Johannes Sorger was awarded this year's OCG sponsorship award.
The paper "Visual and Quantitative Analysis of Higher Order Arborization Overlaps for Neural Circuit Research" was awarded.
The web-based tool "neuroMAP" of VRVis and IMP received the Best Paper Award of the IEEE BioVis 2013.
Visual computing for computer-aided diagnostics and operation planning.
A. Neubauer, M. T. Forster, L. Mroz, R. Wegenkittl, K. Bühler, STEPS - An Application for Simulation of Transsphenoidal Endonasal Pituitary Surgery, in Proceedings of IEEE Visualization 2004, pp 513-520. 2004, IEEE Vis 2004 Best Applications Paper
The European project SUMMER won the award 'Les étoiles de l'Europe'.
Sebastian Zambal, Jiří Hladůvka, Armin Kanitsar, Katja Bühler, Shape and Appearance Models for Automatic Coronary Artery Tracking, WON MICCAI 2008 Contest: 3D Segmentation in Clinic: A Grand Challange.
J. Beyer, M. Hadwiger, S. Wolfsberger), K. Bühler, High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions, in IEEE Transactions on Visualization and Computer Graphics 13(6) pp.1696-1703 / Proceedings of IEEE Vis 2007, Vis 2007 Best Application Paper
A. Neubauer, Endoscopy for Preoperative Planning and Training of Endonasal Transsphenoidal Pituitary Surgery.
C. Langer, M. Hadwiger, K. Bühler, Interaktive diffusionsbasierte Segmentierung von Volumendaten auf Grafikhardware, Bildverarbeitung für die Medizin 2005; GI Informatik Aktuell; Springer Verlag. pp 168-17, BVM 2005 Best Poster
S. Wolfsberger, M. Donat, A. Neubauer, K. Bühler, T. Czech, E. Knosp, Virtuelle Endoskopie in der transsphenoidalen Hypophysenchirurgie, CURAC 2005 Best Poster
M. Meissner, B. Lorensen, K. Zuiderveld, V. Simha, R. Wegenkittl, Volume Rendering in Medical Applications: We've Got Pretty Images, What's Left to Do?, in IEEE Visualization 2002
K. Bühler, Implicit Linear Interval Estimations, in Proceedings of the Spring Conference in Computer Graphics (SCCG'02), ACM Press. pp.123-132, Springer Best Paper
