INSPiRE-MEDINSPIRE-MED INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicine
INSPiRE-MEDINSPIRE-MED INtegrating Magnetic Resonance SPectroscopy and Multimodal Imaging for Research and Education in MEDicine
INSPiRE-MED will provide research and training to 15 early career researchers in the field of medical imaging, specifically Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI), combined with MR Imaging and Positron Emission Tomography (PET). INSPiRE-MED Fellows will acquire skills to develop careers contributing to innovative technological advances in medical imaging in a multi-disciplinary environment encompassing physics, mathematical and computer sciences leading to applications in medicine and biological sciences. The 12 academic and 9 industrial partners will provide the Fellows with transferable and generic skills as well as a comprehensive, wide-ranging education on the basic principles of medical imaging and image analysis. This fundamental knowledge will be combined with in-depth learning in a specific area, through local delivery via graduate schools, programme-wide INSPiRE-MED training activities and workshops and personal academic supervision by two INSPiRE-MED supervisors. This will enable them to successfully participate in developing new tools for clinicians. MRS is a unique, non-invasive molecular technique that has proved useful for diagnosis and therapy management in This proposal disease models and patients. Despite its potential, the clinical uptake of MRS has lagged behind that of MRI and PET. Thus, INSPiRE-MED will have 3 objectives, encapsulated in 3 research Work Packages (WP): 1) Development of novel acquisition and processing techniques allowing MRS(I) to become a key tool in medical imaging (WP1); 2) Integration of innovative MRS(I) techniques in several key clinical and pre-clinical applications including a multimodal metabolic approach based on MR/PET (WP2); 3) Translation of most advanced research in MRS(I) and machine learning into clinical routine by means of a fully automatic software suite, building on the well-known jMRUI package (http:// www.jmrui.eu) to provide a prime tool in personalized medicine (WP 3).
Starčuk Zenon - Ústav přístrojové techniky - Akademie věd České republiky, v.v.i.
Cudalbu Cristina - Ecole Polytechnique Federale de Lausanne
Kreis Roland - UNIVERSITAET BERN
Van Huffel Sabine - KATHOLIEKE UNIVERSITEIT LEUVEN
Möller Harald - MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Williams Stephen - THE UNIVERSITY OF MANCHESTER
Heerschap Arend - STICHTING KATHOLIEKE UNIVERSITEIT
ARÚS CARALTÓ CARLES - Universitat Autonoma de Barcelona
Julià-Sapé Margarita - CONSORCIO CENTRO DE INVESTIGACION BIOMEDICA EN RED M.P.
SIMA DIANA - ICOMETRIX NV
Klomp Dennis - MR COILS BV
Horn Felix - SIEMENS HEALTHCARE GMBH
Geerts Liesbeth - PHILIPS MEDICAL SYSTEMS NEDERLAND BV
Schulte Rolf - GENERAL ELECTRIC DEUTSCHLAND HOLDING GMBH
Heidenreich Michael - BRUKER BIOSPIN MRI GMBH
Virieux Bruno - Fealinx
Frost Bathen Tone - NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU
Gugger Matthias - Insel Gruppe AG
Zimmer Luc - CENTRE D ETUDE ET DE RECHERCHE MULTIMODAL
Haase Jurgen - UNIVERSITAET LEIPZIG