Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Tournier, Pierre-Henri Hecht, Frédéric Nataf, Frédéric Bonazzoli, Marcella Rapetti, Francesca Dolean, Victorita Semenov, Serguie El Kanfoud, Ibtissam Aliferis, Ioannis Migliaccio, Claire
...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

Mourya, Rahul Ferrari, André Flamary, Rémi Bianchi, Pascal Richard, Cédric

Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational photography. In applications such as astronomy and satelliteimaging, the size of acquired images can be extremely lar...

Mourya, Rahul Ferrari, André Flamary, Rémi Bianchi, Pascal Richard, Cédric

Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational photography. In applications such as astronomy and satelliteimaging, the size of acquired images can be extremely lar...

Mourya, Rahul Ferrari, André Flamary, Rémi Bianchi, Pascal Richard, Cédric

Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational photography. In applications such as astronomy and satelliteimaging, the size of acquired images can be extremely lar...

Mourya, Rahul Ferrari, André Flamary, Rémi Bianchi, Pascal Richard, Cédric

Image deblurring is an economic way to reduce certain degradations (blur and noise) in acquired images. Thus, it has become essential tool in high resolution imaging in many applications, e.g., astronomy, microscopy or computational photography. In applications such as astronomy and satelliteimaging, the size of acquired images can be extremely lar...