| People | Locations | Statistics |
|---|---|---|
| Naji, M. |
| |
| Motta, Antonella |
| |
| Aletan, Dirar |
| |
| Mohamed, Tarek |
| |
| Ertürk, Emre |
| |
| Taccardi, Nicola |
| |
| Kononenko, Denys |
| |
| Petrov, R. H. | Madrid |
|
| Alshaaer, Mazen | Brussels |
|
| Bih, L. |
| |
| Casati, R. |
| |
| Muller, Hermance |
| |
| Kočí, Jan | Prague |
|
| Šuljagić, Marija |
| |
| Kalteremidou, Kalliopi-Artemi | Brussels |
|
| Azam, Siraj |
| |
| Ospanova, Alyiya |
| |
| Blanpain, Bart |
| |
| Ali, M. A. |
| |
| Popa, V. |
| |
| Rančić, M. |
| |
| Ollier, Nadège |
| |
| Azevedo, Nuno Monteiro |
| |
| Landes, Michael |
| |
| Rignanese, Gian-Marco |
|
Andriulli, Francesco
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (3/3 displayed)
- 2020A Regularized Electric Flux Volume Integral Equation for Brain Imagingcitations
- 2017A Scaling-Less Newton-Raphson Pipelined Implementation for a Fixed-Point Reciprocal Operatorcitations
- 2017A scaling-less Newton-Raphson pipelined implementation for a fixed-point inverse square root operatorcitations
Places of action
| Organizations | Location | People |
|---|
document
A Regularized Electric Flux Volume Integral Equation for Brain Imaging
Abstract
Volume integral equations for modeling biological tissues in the frequency domain typically suffer from ill-conditioning for high dielectric contrasts and low frequencies. These conditioning breakdowns severely compromise the accuracy and applicability of these models and render them impractical despite their numerous advantages. In this work, we present an electric flux volume integral equation (D-VIE) free from these shortcomings when computed on biologically compatible simply connected objects. This new formulation leverages on careful spectral analysis to obtain volume quasi-Helmholtz projectors capable of curing both sources of ill-conditioning. In particular, the normalization of the projectors by the material permittivity allows for an inhomogeneous re-scaling of the equation which stabilises the high contrast breakdown together with the low-frequency breakdown. Numerical results show the applicability of this new formulation in realistic brain imaging.