Project description DEENESFRITPL Novel tomographic imaging technology is riding the wave Tomography, a combination of the Greek words for 'incision' or 'cutting' and 'writing', is an important technique that produces images of sections or slices through a material. One can focus on a specific plane of interest or combine the planes to recreate a 3D image of, for example, an organ or tissue. Current methods for collecting the data and producing the tomographic images contain a significant amount of uncertainty. The EU-funded QUANTOM project is combining multiple wave modalities including light, microwaves and sound to enable high-resolution quantitative tomographic images, combined with information of the underlying uncertainties. Show the project objective Hide the project objective Objective Tomographic images are a valuable tool in various applications of medicine and biomedicine, industry and in security applications. Although efficient tomographic imaging techniques exist, development of new modalities that would overcome the limitations of the existing techniques are required. Overall, there is a need for development of new tomographic techniques that would provide quantitative information of unknown parameters of interest, such as tomographic images on the concentration of molecules. In particular, information on the reliability of the tomographic images is required. The objective of the project is to develop quantitative tomographic imaging technique based on coupled physics of waves. In coupled physics imaging, contrast and resolution originating from different physical phenomena are combined. In the project, light, microwaves and ultrasound, i.e. waves, will be utilised through photoacoustic, thermoacoustic and acousto-optic effects. These techniques will be developed to produce tomographic images with an outstanding quantitative contrast in the sense of statistical information and modelling of uncertainties, combined with superior resolution and imaging depth. Most tomographic imaging techniques are ill-posed problems that need to be approached in the framework of inverse problems. In the project, a Bayesian approach to ill-posed inverse problems, which supports the quantitative nature of the problem, will be taken. In the project, mathematical modelling and computational methods will be developed in close connection with experimental system development. The research is founded on a strong understanding of the underlying physics of coupled physics problems, knowledge on instrumentation on the related fields and experimental tomography, and state-of-the-art methods of computational inverse mathematics, that all come together in the PI’s research group. Fields of science natural sciencesmathematicsapplied mathematicsstatistics and probabilitybayesian statisticsnatural sciencescomputer and information sciencescomputational sciencemultiphysicsnatural sciencesmathematicsapplied mathematicsmathematical model Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2020-COG - ERC CONSOLIDATOR GRANTS Call for proposal ERC-2020-COG See other projects for this call Funding Scheme ERC-COG - Consolidator Grant Coordinator ITA-SUOMEN YLIOPISTO Net EU contribution € 2 000 000,00 Address Yliopistonranta 1 e 70211 Kuopio Finland See on map Region Manner-Suomi Pohjois- ja Itä-Suomi Pohjois-Savo Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all ITA-SUOMEN YLIOPISTO Finland Net EU contribution € 2 000 000,00 Address Yliopistonranta 1 e 70211 Kuopio See on map Region Manner-Suomi Pohjois- ja Itä-Suomi Pohjois-Savo Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
