Correlated Multimodal Imaging in Life Sciences (COMULIS)

COST – European Cooperation in Science and Technology

Suradnici na projektu:

Ivana Vrhovac Madunić – MC member (Management Committee)

– Grant Awarding Coordinator

– Coordinator for Grant Awarding ITC (Inclusiveness Target


Dean Karaica – MC member (Management Committee)


Duration: 2018-2022

Project leader (MC Chair): Andreas Walter

Sažetak: The network aims at fueling urgently needed collaborations in the field of correlated multimodal imaging (CMI), promoting and disseminating its benefits through showcase pipelines, and paving the way for its technological advancement and implementation as a versatile tool in biological and preclinical research. 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, and instrument developers and users. Due to its inherently multidisciplinary and cross-functional nature, an interdisciplinary network such as this Action is indispensable for the success of CMI. Nevertheless, there is currently no European network in the field. Existing scattered efforts focus on correlated light and electron microscopy or (pre)clinical hybrid imaging. This Action will consolidate these efforts, 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.