CMI combines two or more imaging modalities to gather information about the same specimen. It creates a composite view of the sample with multidimensional information about its macro-, meso- and microscopic structure, dynamics, function and chemical composition.
Since no single imaging technique can reveal all these details, CMI is the only way to understand biomedical processes and diseases mechanistically and holistically. CMI relies on the joint multidisciplinary expertise from biologists, physicists, chemists, clinicians and computer scientists, and depends on coordinated activities and knowledge transfer between academia and industry, as well as instrument developers and users. VRVis is part of the COMULIS initiative, which will establish commonly accepted protocols and quality standards for existing CMI approaches, identify and showcase novel CMI pipelines, bridge the gap between preclinical and biological imaging, and foster correlation software through networking, workshops and open databases. The network will raise awareness for CMI, train researchers in multimodal approaches, and work towards a scientific mindset that is enthusiastic about interdisciplinary imaging approaches in life sciences.
Scientific Director | Head of Biomedical Image Informatics Group, Biomedical Image Informatics
buehler(at)vrvis.at +43 1 908 98 92 401Start: 04.2018
End Date: 03.2022
Coordinator: Andreas Walter, Austrian Bioimaging; Members from all over Europe
EU COST – European Coorperation in Science and Technology
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.