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

doi:10.1109/APUSNCURSINRSM.2017.8072057

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

Ocean, Air and Space

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

15 Citations (Scopus)

70 Downloads (Pure)

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.

Original language	English
Title of host publication	2017 IEEE Antennas and Propagation Society International Symposium, Proceedings
Pages	29-30
Number of pages	2
Volume	2017-January
ISBN (Electronic)	9781538632840
DOIs	https://doi.org/10.1109/APUSNCURSINRSM.2017.8072057
Publication status	Published - 18 Oct 2017
Event	2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017 - San Diego, United States Duration: 9 Jul 2017 → 14 Jul 2017

Conference

Conference	2017 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2017
Country/Territory	United States
City	San Diego
Period	9/07/17 → 14/07/17

Keywords

brain strokes
inverse problems
microwave imaging
microwave tomography
parallel computing

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10.1109/APUSNCURSINRSM.2017.8072057

Tournier-etal-IEEE2017-Microwave-tomography-brain-stroke-imagingAccepted author manuscript, 3.46 MB

Cite this

Tournier, P. H., 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, pp. 29-30) https://doi.org/10.1109/APUSNCURSINRSM.2017.8072057

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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",

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pages = "29--30",

booktitle = "2017 IEEE Antennas and Propagation Society International Symposium, Proceedings",

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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, 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

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AU - Tournier, P. H.

AU - Hecht, F.

AU - Nataf, F.

AU - Semenov, S.

AU - Bonazzoli, M.

AU - Rapetti, F.

AU - Dolean, V.

AU - El Kanfoud, I.

AU - Aliferis, I.

AU - Migliaccio, C.

AU - Pichot, Ch

PY - 2017/10/18

Y1 - 2017/10/18

N2 - 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.

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.

KW - brain strokes

KW - inverse problems

KW - microwave imaging

KW - microwave tomography

KW - parallel computing

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U2 - 10.1109/APUSNCURSINRSM.2017.8072057

DO - 10.1109/APUSNCURSINRSM.2017.8072057

M3 - Conference contribution book

AN - SCOPUS:85042212497

VL - 2017-January

SP - 29

EP - 30

BT - 2017 IEEE Antennas and Propagation Society International Symposium, Proceedings

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Y2 - 9 July 2017 through 14 July 2017

ER -

Microwave tomography for brain stroke imaging

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