Detection of Simulated Brain Strokes Using Microwave Tomography - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Année : 2019

Detection of Simulated Brain Strokes Using Microwave Tomography

Résumé

Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. The ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, thus the nature of the stroke must be determined quickly in order to apply the appropriate treatment. Recent studies in biomedical imaging have shown that strokes produce variations in the complex electric permittivity of brain tissues, which can be detected by means of microwave tomography. Here we present some synthetic results obtained with an experimental microwave tomography-based portable system for the early detection and monitoring of brain strokes. The determination of electric permittivity first requires the solution of a coupled forward-inverse problem. We make use of massive parallel computation from domain decomposition method and regularization techniques for optimization methods. Synthetic data are obtained with electromagnetic simulations corrupted by noise, which have been derived from measurements errors of the experimental imaging system. Results demonstrate the possibility to detect hemorrhagic strokes with microwave systems when applying the proposed reconstruction algorithm with edge preserving regularization.
Fichier principal
Vignette du fichier
JERM.pdf (11.14 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02149100 , version 1 (30-08-2019)

Identifiants

Citer

Vanna Lisa Coli, Pierre-Henri Tournier, Victorita Dolean-Maini, Ibtissam El Kanfoud, Christian Pichot, et al.. Detection of Simulated Brain Strokes Using Microwave Tomography. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, 2019, 1, pp.1. ⟨10.1109/JERM.2019.2921076⟩. ⟨hal-02149100⟩
280 Consultations
96 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More