IPID5180477. Several research teams around the world are currently involved in developing imaging systems, with different specific final objectives and considered modalities. Although excellent results have been reported in the scientific literature (see, for example, [1], [2], and the references therein), there are theoretical and practical difficulties that still make these techniques a challenge. The former are related to the processing of data (limited amount of information, low signal-to-noise ratios, ill-posedness, etc.), whereas the latter are essentially related to the effective realization and use of the system. In this paper, we discuss some recent results related to a tomographic system which is currently under development. In particular, a new reconstruction procedure based on a conjugate gradient approach, directly implemented in the framework of the $L^{p}$ Banach spaces, is presented. This inversion procedure, preliminary discussed in [3], seems to be particularly suitable for obtaining a regularized solution of the inverse scattering problem, with less artefacts and noise (on the final image) due to a reduction of the usually encountered over-smoothing effects. The effectiveness of the approach is evaluated, even with three-dimensional data, by means of numerical simulations involving an accurate model of the human head.
[1]
Francesca Rapetti,et al.
Numerical Modeling and High-Speed Parallel Computing: New Perspectives on Tomographic Microwave Imaging for Brain Stroke Detection and Monitoring.
,
2017,
IEEE Antennas and Propagation Magazine.
[2]
Matteo Pastorino,et al.
Electromagnetic biomedical imaging in Banach spaces: A numerical case study
,
2017,
2017 XXXIInd General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS).
[3]
Igor Bisio,et al.
A numerical study concerning brain stroke detection by microwave imaging systems
,
2018,
Multimedia Tools and Applications.
[4]
Amin M. Abbosh,et al.
Fast Frequency-Based Multistatic Microwave Imaging Algorithm With Application to Brain Injury Detection
,
2016,
IEEE Transactions on Microwave Theory and Techniques.