Faithful non-linear imaging from only-amplitude measurements of incident and total fields.

Applicability of inverse scattering based imaging procedures can be broadened by developing new approaches exploiting only amplitude data. As a matter of fact, this can open the way to simpler and less expensive measurement set-ups. In this respect, a two-step based procedure for solving electromagnetic nonlinear inverse scattering problems from only amplitude measurements of the total field has been recently proposed [1,2]. However, in these latter both amplitude and phase of the incident field are still required. In this contribution, we show the possibility of achieving this information from the measured amplitude distribution of the incident field on the observation domain. In particular, a three steps imaging technique which exploits only amplitude measurements of the total and incident fields has been developed. The proposed procedure has been tested against benchmark experimental data available in the literature. The obtained results fully confirm the possibility of achieving faithful reconstructions of unknown targets without performing any phase measurements and any approximation on the scattering equations involved in the inverse scattering problems

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

This paper presents a novel method for three-dimensional microwave imaging based on sparse processing. To enforce the sparsity of the unknown function, we take advantage of the fact that arbitrary three-dimensional electromagnetic fields can be decomposed into two components with respect to the radial direction: one with transverse-magnetic polarization and the other with transverse-electric polarization. Each component can be further expressed as a sum of spherical harmonics, which provide the dictionary exploited by the sparse processing algorithm. Our measurement model relates the data and the parameters of the spherical harmonics' sources, which are uniformly distributed on a grid sampling the imaging domain. By relying on the theory of degrees of freedom of electromagnetic fields, it can be shown that only a few harmonics are sufficient to accurately represent the measured scattered field from objects whose diameter is of the order of the wavelength, thus allowing reducing the dimension of the adopted dictionary. We analyze several imaging scenarios to assess the algorithm's performance, including different object shapes, sensor orientations, and signal-to-noise ratios. Moreover, we compare the obtained results with other state-of-the-art linear imaging techniques. Notably, thanks to the adopted dictionary, the proposed algorithm can yield accurate images of both convex and concave objects

Hyperthermia Treatment Monitoring via Deep Learning Enhanced Microwave Imaging: A Numerical Assessment

Simple Summary Non-invasive temperature monitoring during hyperthermia cancer treatment is of paramount importance. It allows physicians to verify the therapeutic temperature is reached in the treated area. Currently, only superficial or invasive thermometry is performed on a clinical level. Magnetic resonance thermometry has been proposed as a a non-invasive alternative but its applicability is limited. Conversely, microwave imaging based thermometry is a potential low cost candidate for non-invasive temperature monitoring. This works presents a computational study in which the use of deep learning is proposed to face the challenges related to the use of microwave imaging in hyperthermia monitoring. The paper deals with the problem of monitoring temperature during hyperthermia treatments in the whole domain of interest. In particular, a physics-assisted deep learning computational framework is proposed to provide an objective assessment of the temperature in the target tissue to be treated and in the healthy one to be preserved, based on the measurements performed by a microwave imaging device. The proposed concept is assessed in-silico for the case of neck tumors achieving an accuracy above 90%. The paper results show the potential of the proposed approach and support further studies aimed at its experimental validation

assessing the capabilities of a new linear inversion method for quantitative microwave imaging

We investigate the imaging capabilities of a new linear microwave imaging approach, which allows to quantitative retrieve the complex permittivity distribution of unknown nonweak targets. To this end, we carry out a parametric numerical analysis for a canonical scatterer (a homogeneous dielectric cylinder with circular cross section) and derive a quantitative criterion to foresee the method's applicability. The reliability of the criterion is then tested against noncanonical scatterers to show the effectiveness of the method in imaging nonweak targets and in outperforming the linearized inversion method based on the standard Born approximation

AN ADAPTIVE METHOD TO FOCUSING IN AN UNKNOWN SCENARIO

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An Effective Method for Borehole Imaging of Buried Tunnels

Detection and imaging of buried tunnels is a challenging problem which is relevant to both geophysical surveys and security monitoring. To comply with the need of exploring large portions of the underground, electromagnetic measurements carried out under a borehole configuration are usually exploited. Since this requires to drill holes in the soil wherein the transmitting and receiving antennas have to be positioned, low complexity of the involved apparatus is important. On the other hand, to effectively image the surveyed area, there is the need for adopting efficient and reliable imaging methods. To address these issues, in this paper we investigate the feasibility of the linear sampling method (LSM), as this inverse scattering method is capable to provide almost real-time results even when 3D images of very large domains are built, while not requiring approximations of the underlying physics. In particular, the results of the reported numerical analysis show that the LSM is capable of performing the required imaging task while using a quite simple measurement configuration consisting of two boreholes and a few number of multiview-multistatic acquisitions

THz Imaging for Food Inspections: A Technology Review and Future Trends

Terahertz imaging is the newest among non-invasive sensing technologies and currently huge attention is pointed towards its use in several applications. Among possible applications, food inspection represents one of the most prominent cases, due to the possible dangerous impact on human safety. Hence, significant efforts are currently addressed towards the exploitation of THz imaging as a tool to improve the effectiveness of food quality surveys. This chapter deals with the exploitation of THz imaging technology for food quality control and assessment. In particular, the chapter aims at reviewing the latest developments regarding THz imaging, both in terms of measurement systems and data processing methodologies. Moreover, the chapter summarizes experiments available in literature and presents some purposely designed experiments to address the discussion on currently open issues

Multi-Antenna System for In-Line Food Imaging at Microwave Frequencies

This work presents the design and numerical assessment of a novel microwave imaging (MWI) system, capable of providing a full 3-D image of food/beverage products content in order to disclose the possible presence of physical contaminants, such as plastic fragments. The system here presented exploits the dielectric contrast between the food content and possible intrusions at microwave frequencies; it is based on an antenna array architecture inspecting the items in motion along a conveyor belt without interrupting the production process. The inversion problem is solved by means of linearization, assuming the viability of the Born approximation thanks to the localized intrusions, and regularization, based on the singular value decomposition of the discretized scattering operator. Furthermore, an algorithm, to balance the illumination of the considered scenario due to the nonuniform radiation of the employed antennas, is presented to enhance imaging. The system is first assessed considering an ideal case and then extended to a more realistic approach, for two different kinds of food products, with completely different dielectric properties and considering the performance of existing instrumentation for the purpose. The obtained results lay the foundations for the realization of an actual prototype