@inproceedings{a6a6e4a0c5724de5a123c761f98161ba,
title = "Microwave tomography for brain stroke imaging",
abstract = "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 wholemicrowave 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.",
keywords = "Brain Strokes, Inverse Problems, Microwave Imaging, Microwave Tomography, Parallel computing",
author = "Tournier, \{P. H.\} and F. Hecht and F. Nataf and S. Semenov and M. Bonazzoli and F. Rapetti and V. Dolean and \{El Kanfoud\}, I. and I. Aliferis and C. Migliaccio and Ch Pichot",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017 ; Conference date: 09-07-2017 Through 14-07-2017",
year = "2017",
month = oct,
day = "18",
doi = "10.1109/APUSNCURSINRSM.2017.8072057",
language = "English",
series = "2017 IEEE Antennas and Propagation Society International Symposium, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "29--30",
booktitle = "2017 IEEE Antennas and Propagation Society International Symposium, Proceedings",
}