Microwave tomography for brain stroke imaging

P. H. Tournier, F. Hecht, F. Nataf, S. Semenov, M. Bonazzoli, F. Rapetti, V. Dolean, I. El Kanfoud, I. Aliferis, C. Migliaccio, Ch Pichot

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

2 Citations (Scopus)

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.

LanguageEnglish
Title of host publication2017 IEEE Antennas and Propagation Society International Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-30
Number of pages2
Volume2017-January
ISBN (Electronic)9781538632840
DOIs
Publication statusPublished - 18 Oct 2017
Event2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017 - San Diego, United States
Duration: 9 Jul 201714 Jul 2017

Conference

Conference2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017
CountryUnited States
CitySan Diego
Period9/07/1714/07/17

Fingerprint

strokes
brain
Tomography
Brain
tomography
Microwaves
Imaging techniques
microwaves
Domain decomposition methods
Newton methods
Parallel processing systems
Inverse problems
decomposition
gradients
optimization
Monitoring

Keywords

  • brain strokes
  • inverse problems
  • microwave imaging
  • microwave tomography
  • parallel computing

Cite this

Tournier, P. H., Hecht, F., Nataf, F., Semenov, S., Bonazzoli, M., Rapetti, F., ... Pichot, C. (2017). Microwave tomography for brain stroke imaging. In 2017 IEEE Antennas and Propagation Society International Symposium, Proceedings (Vol. 2017-January, pp. 29-30). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APUSNCURSINRSM.2017.8072057
Tournier, P. H. ; Hecht, F. ; Nataf, F. ; Semenov, S. ; Bonazzoli, M. ; Rapetti, F. ; Dolean, V. ; El Kanfoud, I. ; Aliferis, I. ; Migliaccio, C. ; Pichot, Ch. / Microwave tomography for brain stroke imaging. 2017 IEEE Antennas and Propagation Society International Symposium, Proceedings. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 29-30
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Tournier, PH, Hecht, F, Nataf, F, Semenov, S, Bonazzoli, M, Rapetti, F, Dolean, V, El Kanfoud, I, Aliferis, I, Migliaccio, C & Pichot, C 2017, Microwave tomography for brain stroke imaging. in 2017 IEEE Antennas and Propagation Society International Symposium, Proceedings. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 29-30, 2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017, San Diego, United States, 9/07/17. https://doi.org/10.1109/APUSNCURSINRSM.2017.8072057

Microwave tomography for brain stroke imaging. / Tournier, P. H.; Hecht, F.; Nataf, F.; Semenov, S.; Bonazzoli, M.; Rapetti, F.; Dolean, V.; El Kanfoud, I.; Aliferis, I.; Migliaccio, C.; Pichot, Ch.

2017 IEEE Antennas and Propagation Society International Symposium, Proceedings. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 29-30.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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AB - 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.

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Tournier PH, Hecht F, Nataf F, Semenov S, Bonazzoli M, Rapetti F et al. Microwave tomography for brain stroke imaging. In 2017 IEEE Antennas and Propagation Society International Symposium, Proceedings. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 29-30 https://doi.org/10.1109/APUSNCURSINRSM.2017.8072057