Microwave tomography for breast cancer detection within a Variational Bayesian Approach - CICS Accéder directement au contenu
Communication Dans Un Congrès Année : 2013

Microwave tomography for breast cancer detection within a Variational Bayesian Approach

Résumé

We consider a nonlinear inverse scattering problem where the goal is to detect breast cancer from measurements of the scattered field that results from its interaction with a known wave in the microwave frequency range. The modeling of the wave-object interaction is tackled through a domain integral representation of the electric field in a 2D-TM configuration. The inverse problem is solved in a Bayesian framework where the prior information is introduced via a Gauss-Markov-Potts model. A Variational Bayesian Approximation (VBA) technique is adapted to complex valued contrast and applied to compute the posterior estimators and reconstruct maps of both the permittivity and conductivity. Results obtained by means of this approach from synthetic data are compared with those given by a deterministic contrast source inversion method.
Fichier principal
Vignette du fichier
Gharsalli_Leila_Eusipco2013Final.pdf (650.3 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00854799 , version 1 (28-08-2013)

Identifiants

  • HAL Id : hal-00854799 , version 1

Citer

Leila Gharsalli, H Ayasso, Bernard Duchêne, Ali Mohammad-Djafari. Microwave tomography for breast cancer detection within a Variational Bayesian Approach. EUSIPCO 2013 - 21th European Signal Processing Conference, Sep 2013, Marrakech, Morocco. pp.ID1569743387. ⟨hal-00854799⟩
235 Consultations
206 Téléchargements

Partager

Gmail Facebook X LinkedIn More