### Abstract

The motivation of this work is the detection of cerebrovascular accidents by microwave tomographic imaging. This requires the solution of an inverse problem relying on a minimization algorithm (for example, gradient-based), where successive iterations consist in repeated solutions of a direct problem. The reconstruction algorithm is extremely computationally intensive and makes use of efficient parallel algorithms and high-performance computing. The feasibility of this type of imaging is conditioned on one hand by an accurate reconstruction of the material properties of the propagation medium and on the other hand by a considerable reduction in simulation time. Fulfilling these two requirements will enable a very rapid and accurate diagnosis. From the mathematical and numerical point of view, this means solving Maxwell's equations in time-harmonic regime by appropriate domain decomposition methods, which are naturally adapted to parallel architectures.

Language | English |
---|---|

Pages | 88-97 |

Number of pages | 10 |

Journal | Parallel Computing |

Volume | 85 |

Early online date | 25 Feb 2019 |

DOIs | |

Publication status | Published - 31 Jul 2019 |

### Fingerprint

### Keywords

- inverse problem
- Maxwell's equations
- microwave imaging
- scalable preconditioners

### Cite this

*Parallel Computing*,

*85*, 88-97. https://doi.org/10.1016/j.parco.2019.02.004

}

*Parallel Computing*, vol. 85, pp. 88-97. https://doi.org/10.1016/j.parco.2019.02.004

**Microwave tomographic imaging of cerebrovascular accidents by using high-performance computing.** / Tournier, P.-H.; Aliferis, I.; Bonazzoli, M.; Buhan, M. de; Darbas, M.; Dolean, V.; Hecht, F.; Jolivet, P.; El Kanfoud, I.; Migliaccio, C.; Nataf, F.; Pichot, Ch.; Semenov, S.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Microwave tomographic imaging of cerebrovascular accidents by using high-performance computing

AU - Tournier, P.-H.

AU - Aliferis, I.

AU - Bonazzoli, M.

AU - Buhan, M. de

AU - Darbas, M.

AU - Dolean, V.

AU - Hecht, F.

AU - Jolivet, P.

AU - El Kanfoud, I.

AU - Migliaccio, C.

AU - Nataf, F.

AU - Pichot, Ch.

AU - Semenov, S.

PY - 2019/7/31

Y1 - 2019/7/31

N2 - The motivation of this work is the detection of cerebrovascular accidents by microwave tomographic imaging. This requires the solution of an inverse problem relying on a minimization algorithm (for example, gradient-based), where successive iterations consist in repeated solutions of a direct problem. The reconstruction algorithm is extremely computationally intensive and makes use of efficient parallel algorithms and high-performance computing. The feasibility of this type of imaging is conditioned on one hand by an accurate reconstruction of the material properties of the propagation medium and on the other hand by a considerable reduction in simulation time. Fulfilling these two requirements will enable a very rapid and accurate diagnosis. From the mathematical and numerical point of view, this means solving Maxwell's equations in time-harmonic regime by appropriate domain decomposition methods, which are naturally adapted to parallel architectures.

AB - The motivation of this work is the detection of cerebrovascular accidents by microwave tomographic imaging. This requires the solution of an inverse problem relying on a minimization algorithm (for example, gradient-based), where successive iterations consist in repeated solutions of a direct problem. The reconstruction algorithm is extremely computationally intensive and makes use of efficient parallel algorithms and high-performance computing. The feasibility of this type of imaging is conditioned on one hand by an accurate reconstruction of the material properties of the propagation medium and on the other hand by a considerable reduction in simulation time. Fulfilling these two requirements will enable a very rapid and accurate diagnosis. From the mathematical and numerical point of view, this means solving Maxwell's equations in time-harmonic regime by appropriate domain decomposition methods, which are naturally adapted to parallel architectures.

KW - inverse problem

KW - Maxwell's equations

KW - microwave imaging

KW - scalable preconditioners

UR - http://www.scopus.com/inward/record.url?scp=85064325577&partnerID=8YFLogxK

U2 - 10.1016/j.parco.2019.02.004

DO - 10.1016/j.parco.2019.02.004

M3 - Article

VL - 85

SP - 88

EP - 97

JO - Parallel Computing

T2 - Parallel Computing

JF - Parallel Computing

SN - 0167-8191

ER -