C. Dachena, A. Fedeli, A. Fanti, M. B. Lodi, G. Fumera, M. Pastorino, A. Randazzo
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引用次数: 3
Abstract
In this letter, a microwave imaging strategy based on an artificial neural network (ANN) is applied, for the first time, to experimental data gathered from simplified neck phantoms. The ANN is used for solving the underlying inverse scattering problem, with the aim of retrieving the dielectric properties of the neck for monitoring and diagnostic purposes. The ANN is trained using simulated phantoms, to overcome the limited availability of experimental data. First, a simple configuration with a liquid-filled glass beaker is tested. Then, simplified 3-D-printed models of the human neck are considered. The preliminary findings indicate the possibility of training the network with numerical simulations and testing it against experimental measurements.
期刊介绍:
The IEEE Microwave and Wireless Components Letters (MWCL) publishes four-page papers (3 pages of text + up to 1 page of references) that focus on microwave theory, techniques and applications as they relate to components, devices, circuits, biological effects, and systems involving the generation, modulation, demodulation, control, transmission, and detection of microwave signals. This includes scientific, technical, medical and industrial activities. Microwave theory and techniques relates to electromagnetic waves in the frequency range of a few MHz and a THz; other spectral regions and wave types are included within the scope of the MWCL whenever basic microwave theory and techniques can yield useful results. Generally, this occurs in the theory of wave propagation in structures with dimensions comparable to a wavelength, and in the related techniques for analysis and design.