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, gradientbased), 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 highperformance 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 timeharmonic regime by appropriate domain decomposition methods, which are naturally adapted to parallel architectures.
Original language  English 

Pages (fromto)  8897 
Number of pages  10 
Journal  Parallel Computing 
Volume  85 
Early online date  25 Feb 2019 
DOIs  
Publication status  Published  31 Jul 2019 
Keywords
 inverse problem
 Maxwell's equations
 microwave imaging
 scalable preconditioners
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Victorita Dolean Maini
 Health and Wellbeing
 Ocean, Air and Space
 Mathematics And Statistics  Visiting Professor
Person: Visiting Professor