Numerical modeling and high-speed parallel computing : new perspectives on tomographic microwave imaging for brain stroke detection and monitoring

Tournier, Pierre Henri and Bonazzoli, Marcella and Dolean, Victorita and Rapetti, Francesca and Hecht, Frederic and Nataf, Frederic and Aliferis, Iannis and El Kanfoud, Ibtissam and Migliaccio, Claire and De Buhan, Maya and Darbas, Marion and Semenov, Serguei and Pichot, Christian (2017) Numerical modeling and high-speed parallel computing : new perspectives on tomographic microwave imaging for brain stroke detection and monitoring. IEEE Antennas and Propagation Magazine, 59 (5). pp. 98-110. ISSN 1045-9243 (https://doi.org/10.1109/MAP.2017.2731199)

[thumbnail of Tournier-etal-IEEEAPM-2017-Numerical-modeling-and-high-speed-parallel-computing]
Preview
 Text. Filename: Tournier_etal_IEEEAPM_2017_Numerical_modeling_and_high_speed_parallel_computing.pdf
Accepted Author Manuscript
Download (3MB)| Preview

Abstract

This article 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 based) with successive solutions of a direct problem such as the accurate modeling of a whole-microwave measurement system. Moreover, a sufficiently high number of unknowns is required to accurately represent the solution. As the system will be used for detecting a brain stroke (ischemic or hemorrhagic) as well as for monitoring during the treatment, the running times for the reconstructions should be reasonable. The method used is based on high-order finite elements, parallel preconditioners from the domain decomposition method and domain-specific language with the opensource FreeFEM-solver.

  • Item type:Article
    ID code:76886
    Dates:
    Date
    Event
    1 October 2017
    Published
    22 August 2017
    Published Online
    22 August 2017
    Accepted
    Notes:© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:28 Jun 2021 11:49
    Last modified:25 Apr 2024 01:22
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/76886
CORE (COnnecting REpositories)