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).
| 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 | |
| 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 |
Fingerprint
Keywords
- hemorrhaging
- microwave imaging
- permittivity
- microwave theory and techniques
- tomography
- brain modeling
Cite this
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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
TY - GEN
T1 - Detection of brain strokes using microwave tomography
AU - Coli, Vanna Lisa
AU - Tournier, Pierre-Henri
AU - Dolean, Victorita
AU - El Kanfoud, Ibtissam
AU - Pichot, Christian
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.
PY - 2019/1/14
Y1 - 2019/1/14
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).
KW - hemorrhaging
KW - microwave imaging
KW - permittivity
KW - microwave theory and techniques
KW - tomography
KW - brain modeling
UR - http://www.scopus.com/inward/record.url?scp=85061905662&partnerID=8YFLogxK
U2 - 10.1109/APUSNCURSINRSM.2018.8609404
DO - 10.1109/APUSNCURSINRSM.2018.8609404
M3 - Conference contribution book
SN - 9781538671023
SP - 223
EP - 224
BT - 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting - Proceedings
PB - IEEE
CY - Piscataway, NJ
ER -