Correlated Multimodal Imaging in Life Sciences


  • Duration: 4 years
  • Funded by: EU
  • Programme: COST
  • Partners: VBCF (Action Main Proposer, Austria), 33 other countries
  • Total project costs: ~ € 130,000/year
  • Project website:


The network aims to fuel urgently needed collaboration 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 crossfunctional nature, the proposed network is indispensable for the success of CMI. Nevertheless, there is currently no European network in the field. Existing scattered efforts mainly focus on correlated light and electron microscopy or (pre)clinical hybrid imaging. This Action will consolidate their 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 of CMI, train researchers in multimodal approaches, and work towards a scientific mindset that is enthusiastic about interdisciplinary imaging approaches in life sciences.