The BioImaging Austria/CMI consortium is a joint initiative of leading Austrian imaging experts to foster and pioneer correlated multimodal imaging in life sciences. CMI offers a multitude of state-of-the-art imaging technologies for organic materials, biomedical model organisms and humans, numerous multimodal imaging pipelines, and various support services, such as data and image analysis, to scientists on a national and international level.
Imaging techniques at CMI span the entire resolution range of interest for (pre)clinical and biological studies, and provide complementary sample information about structure, function, dynamics and chemical composition. More than 35 imaging techniques allow both in- and ex-vivo imaging and molecular analysis.
CMI is developing entirely new multimodal workflows at the forefront of correlated imaging, which can involve more than two imaging modalities – and hence significantly advances the field of correlated imaging with truly holistic approaches. International customers and users are supervised, trained and supported by highly skilled technicians and scientists.
Scientific Director | Head of Biomedical Image Informatics Group, Biomedical Image Informatics
buehler(at)vrvis.at +43 1 908 98 92 401Start: 2015
End Date: -
Medical University of Vienna (MedUni), Vienna Biocenter Core Facilities GmbH (VBCF), TU Wien, VetMed Uni Wien, VRVis LBI Trauma, AIT, FH Upper Austria, University of Vienna, IST Austria
COMULIS is an EU-funded COST Action that aims at fueling collaborations in the field of correlated multimodal imaging (CMI).
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.
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.
Visual computing techniques for the automated detection of osteoporosis and osteoarthritis.
Software for the use of multi-modality images in external radiotherapy.
The analysis, visualization and exploration of high-dimensional image spaces are the subject of the KAFus project.