COmputatioNal Imaging as a training network for Smart biomedical dEvices
The project’s vision is to develop novel, unconventional techniques for multi-dimensional biomedical optical imaging for the detection and mapping of absorption, scattering, and fluorescence, in biological tissues using visible and near-infrared light. The possibility of detecting other dimensions like time and wavelength, together with space, dramatically improves the imaging and diagnostic power of biomedical devices. So far, this capability is strongly hampered by the fact that most work on biomedical instrumentation focuses on maximising the number of measurements (pixel, raster scans, etc.) regardless of the information content, thus leading to a huge amount of data to manage, transfer and analyse, resulting in a significant gap between measurement and result.
CONcISE will overcome these limitations thanks to an outstanding research and training programme based on the vision that (i) a system as a whole includes both hardware and software that are fully integrated and (ii) acquisition and detection are piloted by information content derived by the sample under an adaptive, data-driven framework. Following this approach, the CONcISE Doctoral Candidates will be capable of leading and boosting the biomedical imaging industry towards the development of a new generation of devices, with a strong impact on the biomedical imaging sector and healthcare in general.
The CONcISE Doctoral Network will provide the Doctoral Candidates with a unique, advanced, multi-disciplinary training programme covering all aspects of biomedical imaging science: modelling, design, development, data analysis, validation and translation to the application.
This project contributes to the UN Sustainable Development Goals (SDGs) 3, 4 and 9.
Consiglio Nazionale delle Ricerche, IT
Partners:
- Itae-Suomen yliopisto, FI
- Politecnico di Milano, IT
- Universitat Jaume I De Castellon, ES
- Stichting Nederlandse Wetenschappelijk Onderzoek Instituten, NL
- FYLA Laser S.L., ES
- University College London, UK
- Intuitive Surgical Sàrl, CH
- ViALUX GmbH, DE
- Datrix SpA, IT
- Universite de Strasbourg, FR
- accelopment Schweiz AG, CH
