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Microwave tomographic imaging of cerebrovascular accidents by using high-performance computing
Univ Paris Diderot SPC, Sorbonne Univ, Lab Jacques Louis Lions, CNRS,Inria,Equipe Alpines, F-75005 Paris, France..
Univ Cote dAzur, CNRS, LEAT, Nice, France..
Ecole Polytech, CMAP, INRIA Saclay Ile France, Palaiseau, France..
Univ Paris 05, Sorbonne Paris Cite, UMR CNRS 8145, MAP5, Paris, France..
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2019 (English)In: Parallel Computing, ISSN 0167-8191, E-ISSN 1872-7336, Vol. 85, p. 88-97Article in journal (Refereed) Published
Abstract [en]

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. 

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2019. Vol. 85, p. 88-97
Keywords [en]
inverse problem, Scalable preconditioners, Maxwell's equations, Microwave imaging
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-44669DOI: 10.1016/j.parco.2019.02.004ISI: 000471087700008OAI: oai:DiVA.org:mdh-44669DiVA, id: diva2:1331724
Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-27Bibliographically approved

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