Microwave tomography for brain stroke imaging

Pierre-Henri Tournier (1) , Frédéric Hecht (1) , Frédéric Nataf (1) , Marcella Bonazzoli (2) , Francesca Rapetti (2) , Victorita Dolean (3, 2) , Serguei Semenov (4) , Ibtissam El Kanfoud (3) , Ioannis Aliferis (3) , Claire Migliaccio (3) , Christian Pichot (3)

1 LJLL - Laboratoire Jacques-Louis Lions
2 LJAD - Laboratoire Jean Alexandre Dieudonné
3 LEAT - Laboratoire d'Electronique, Antennes et Télécommunications
4 EMTensor GmbH

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. The solution direct requests an accurate modeling of the whole-microwave measurement system as well as the as the whole-head. Moreover, as the system will be used for detecting brain strokes (ischemic or hemorrhagic) and for monitoring during the treatment, running times for the reconstructions should be fast. The method used is based on high-order finite elements, parallel preconditioners with the Domain Decomposition method and Domain Specific Language with open source FreeFEM++ solver.

Mots clés: Microwave Imaging; iterative methods; medical image processing; computerised tomography; massively parallel computing; Newton method; biomedical imaging; brain; inverse problem; direct problem; iterative microwave; brain stroke imaging; image reconstruction; finite element analysis; Antenna measurements; Microwave theory and techniques; Permittivity; Tomography; Brain Strokes; Parallel computing; Microwave Tomography; Newton-like methods; Inverse Problems; microwave measurement; numerical modeling; whole-microwave measurement system

Domaines: Electromagnétisme

Pierre-Henri Tournier, Frédéric Hecht, Frédéric Nataf, Marcella Bonazzoli, Francesca Rapetti, et al.. Microwave tomography for brain stroke imaging. 2017 IEEE International Symposium on Antennas and Propagation USNC/URSI National Radio Science Meeting, Jul 2017, San Diego, United States. pp.29-30, ⟨10.1109/APUSNCURSINRSM.2017.8072057⟩. ⟨hal-01623136⟩