Detection of brain strokes using microwave tomography

Vanna Lisa Coli, Pierre-Henri Tournier, Victorita Dolean, Ibtissam El Kanfoud, Christian Pichot, Claire Migliaccio, Laure Blanc-Féraud

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

Abstract

Brain stroke is a major cause of disability and death worldwide. There are two types of stroke, ischemic or cerebral infarction (85% of cases) and hemorrhagic (15%). The diagnosis must be made quickly (within 3 to 4 hours after the onset of symptoms) to determine the nature of the stroke and proceed to treatment. Recent works have shown the modification of the complex permittivity according to the nature of stroke [1] in the microwave domain. We are interested here in the detection of brain strokes using microwave tomography. We present results obtained by electromagnetic simulations coupled to a realistic noise model of measurements. The forward problem is based on a massively parallel computing using domain decomposition method, and an inverse problem based on L-BFGS algorithm with a regularization based on total variation (TV).

LanguageEnglish
Title of host publication2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages223-224
Number of pages2
ISBN (Print)9781538671023
DOIs
Publication statusPublished - 14 Jan 2019
Event2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Boston, United States
Duration: 8 Jul 201813 Jul 2018

Conference

Conference2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018
CountryUnited States
CityBoston
Period8/07/1813/07/18

Fingerprint

strokes
brain
Tomography
Brain
tomography
Microwaves
microwaves
Domain decomposition methods
Parallel processing systems
Inverse problems
Permittivity
infarction
disabilities
death
permittivity
electromagnetism
decomposition
causes
simulation

Keywords

  • hemorrhaging
  • microwave imaging
  • permittivity
  • microwave theory and techniques
  • tomography
  • brain modeling

Cite this

Coli, V. L., Tournier, P-H., Dolean, V., El Kanfoud, I., Pichot, C., Migliaccio, C., & Blanc-Féraud, L. (2019). Detection of brain strokes using microwave tomography. In 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings (pp. 223-224). [8609404] Piscataway, NJ: IEEE. https://doi.org/10.1109/APUSNCURSINRSM.2018.8609404
Coli, Vanna Lisa ; Tournier, Pierre-Henri ; Dolean, Victorita ; El Kanfoud, Ibtissam ; Pichot, Christian ; Migliaccio, Claire ; Blanc-Féraud, Laure. / Detection of brain strokes using microwave tomography. 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings. Piscataway, NJ : IEEE, 2019. pp. 223-224
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abstract = "Brain stroke is a major cause of disability and death worldwide. There are two types of stroke, ischemic or cerebral infarction (85{\%} of cases) and hemorrhagic (15{\%}). The diagnosis must be made quickly (within 3 to 4 hours after the onset of symptoms) to determine the nature of the stroke and proceed to treatment. Recent works have shown the modification of the complex permittivity according to the nature of stroke [1] in the microwave domain. We are interested here in the detection of brain strokes using microwave tomography. We present results obtained by electromagnetic simulations coupled to a realistic noise model of measurements. The forward problem is based on a massively parallel computing using domain decomposition method, and an inverse problem based on L-BFGS algorithm with a regularization based on total variation (TV).",
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Coli, VL, Tournier, P-H, Dolean, V, El Kanfoud, I, Pichot, C, Migliaccio, C & Blanc-Féraud, L 2019, Detection of brain strokes using microwave tomography. in 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings., 8609404, IEEE, Piscataway, NJ, pp. 223-224, 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018, Boston, United States, 8/07/18. https://doi.org/10.1109/APUSNCURSINRSM.2018.8609404

Detection of brain strokes using microwave tomography. / Coli, Vanna Lisa; Tournier, Pierre-Henri; Dolean, Victorita; El Kanfoud, Ibtissam; Pichot, Christian; Migliaccio, Claire; Blanc-Féraud, Laure.

2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings. Piscataway, NJ : IEEE, 2019. p. 223-224 8609404.

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

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AU - Blanc-Féraud, Laure

N1 - © 2019 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.

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N2 - Brain stroke is a major cause of disability and death worldwide. There are two types of stroke, ischemic or cerebral infarction (85% of cases) and hemorrhagic (15%). The diagnosis must be made quickly (within 3 to 4 hours after the onset of symptoms) to determine the nature of the stroke and proceed to treatment. Recent works have shown the modification of the complex permittivity according to the nature of stroke [1] in the microwave domain. We are interested here in the detection of brain strokes using microwave tomography. We present results obtained by electromagnetic simulations coupled to a realistic noise model of measurements. The forward problem is based on a massively parallel computing using domain decomposition method, and an inverse problem based on L-BFGS algorithm with a regularization based on total variation (TV).

AB - Brain stroke is a major cause of disability and death worldwide. There are two types of stroke, ischemic or cerebral infarction (85% of cases) and hemorrhagic (15%). The diagnosis must be made quickly (within 3 to 4 hours after the onset of symptoms) to determine the nature of the stroke and proceed to treatment. Recent works have shown the modification of the complex permittivity according to the nature of stroke [1] in the microwave domain. We are interested here in the detection of brain strokes using microwave tomography. We present results obtained by electromagnetic simulations coupled to a realistic noise model of measurements. The forward problem is based on a massively parallel computing using domain decomposition method, and an inverse problem based on L-BFGS algorithm with a regularization based on total variation (TV).

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Coli VL, Tournier P-H, Dolean V, El Kanfoud I, Pichot C, Migliaccio C et al. Detection of brain strokes using microwave tomography. In 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings. Piscataway, NJ: IEEE. 2019. p. 223-224. 8609404 https://doi.org/10.1109/APUSNCURSINRSM.2018.8609404