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

• Published in: Parallel computing Vol. 85; pp. 88 - 97
• Main Authors: 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.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2019; Elsevier
• Subjects: Electromagnetism; Engineering Sciences; Inverse problem; Mathematics; Maxwell's equations; Microwave imaging; Numerical Analysis; Scalable preconditioners; Scalable preconditioners; Maxwell’s equations; Inverse problem; Microwave imaging; Maxwell's equations
• ISSN: 0167-8191; 1872-7336; 1872-7336
• DOI: 10.1016/j.parco.2019.02.004

•Feasibility of a microwave tomographic imaging technique for brain strokes.•Scalable domain decomposition solver for Maxwell’s equations on thousands of cores.•Implementation of a nonlinear optimization algorithm in a parallel framework.•Synthetic data generated from a very accurate virtual head model. 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.