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

doi:10.1109/APUSNCURSINRSM.2018.8609404

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 proceeding › Conference contribution book

2 Citations (Scopus)

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).

Original language	English
Title of host publication	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	223-224
Number of pages	2
ISBN (Print)	9781538671023
DOIs	https://doi.org/10.1109/APUSNCURSINRSM.2018.8609404
Publication status	Published - 14 Jan 2019
Event	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Boston, United States Duration: 8 Jul 2018 → 13 Jul 2018

Conference

Conference	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018
Country	United States
City	Boston
Period	8/07/18 → 13/07/18

Keywords

hemorrhaging
microwave imaging
permittivity
microwave theory and techniques
tomography
brain modeling

Access to Document

10.1109/APUSNCURSINRSM.2018.8609404

Coli-etal-IEEE-2019-Detection-of-brain-strokes-using-microwave-tomographyAccepted author manuscript, 6.4 MB

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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] 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).",

keywords = "hemorrhaging, microwave imaging, permittivity, microwave theory and techniques, tomography, brain modeling",

author = "Coli, {Vanna Lisa} and Pierre-Henri Tournier and Victorita Dolean and {El Kanfoud}, Ibtissam and Christian Pichot and Claire Migliaccio and Laure Blanc-F{\'e}raud",

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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 proceeding › Conference contribution book

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AU - Migliaccio, Claire

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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