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This paper proposes an innovative technique to calibrate microwave imaging (MWI) systems combining available measured data with simulated synthetic ones. The introduced technique aims to compensate the variations of the antenna array due to unavoidable manufacturing tolerances and placement, in comparison to the nominal electromagnetic (EM) scenario. The scheme is tested virtually and experimentally for the MWI of the adult human head tissues. The virtual EM analysis uses a realistic 3-D CAD model working together with a full-wave software, based on the finite element method. Meanwhile, the real implementation employs a single-cavity anthropomorphic head phantom and a custom brick-shaped antenna array working at around 1 GHz.

Quality control is of great importance in food industry, both for the evaluation of product characteristics and to avoid the occurrence of foreign bodies contamination in packaged items. With respect to the inspections against possible contaminants inside the product, different technologies are currently adopted along production chain lines. However, the number of accidents involving low density objects remains very large. To overcome this limitation, the use of electromagnetic technologies has been recently proposed. In this work, the synergic use of terahertz and microwaves technologies is proposed, so to provide high resolution images and in-depth inspections of different scenarios, including low density materials. A focus study on sugar samples is considered, reporting both its broadband characterization at microwaves and preliminary terahertz imaging to evaluate the integrity of the packaging. Ongoing research is devoted to the development and validation of a microwave device for monitoring food products along the production line.

In this paper we propose to study the dispersion diagram of non-canonical glide-symmetric unit cells via integral equations with the use of the periodic Green’s function and discretized via the method of moment. The proposed approach is validated with a fully metallic implementation of a Luneburg lens operating at Ka-band with potential use for 5G communications. The promising preliminary numerical results highlight the potentialities of this approach.

Towards a preclinical prototype for diagnostic and monitoring of cerebral pathologies, here we present the 3D electromagnetic (EM) virtual prototyping of different clinical scenarios as an instrument for studying the interaction of biological tissues with EM waves, for designing a microwave brain imaging scanner and for generating a set EM fields usually required by imaging algorithms. We employ a full-wave modelling, which uses a Method of Moment (MoM) solver with high order basis functions and includes frequency variable electrical parameters for each component. The model of the microwave imaging system consists of 24-element conformal antennas, an anthropomorphic adult human head, and a spherical shape blood-filled as stroke. Here, the simulated system and data are tested applying an imaging algorithm based on Truncated Singular Value Decomposition (TSVD) and Born approximation, but they can be combined with other microwave imaging algorithms.

Brain stroke is one of the most common diseases worldwide. Magnetic resonance imaging and computerized tomography are currently the two most assessed and reliable diagnostic tools, of great support to the clinicians. However, these devices are costly, time consuming and not portable, so that they are not appropriate for bedside monitoring. Hence, there is an increasing worldwide interest to develop complementary techniques to continuously monitor a patient after the stroke onset. In this paper, we report about the experimental testing of a novel device able to monitor cerebrovascular diseases, whose realization is based on microwave imaging technology. A 2-D version of the device has been fully experimentally tested and its 3-D version is under development.

Foreign body contamination in food is one of the major sources of complaints against food manufacturers, and it can lead to injury, loss of brand loyalty and large recall expenses. Different technologies, such as X-ray or infrared techniques, are currently applied to detection systems used for food inspection, but physical contamination, with e.g. wood, plastic, metal and glass fragments, is still present in food. For this reason, there is the interest to develop new technologies able to address the still unmet needs of food industry. In this paper, we report about preliminary investigations of the use of the microwave imaging technology for food contamination monitoring. Numerical results show the feasibility of the proposed approach. The realization of prototype measurement system is under development.

International audience; Food quality earns a huge interest from food industry. In particular, the presence of small foreign fragments is generally the main issue in food quality control. While metal contaminants can be detected by means of metal detectors, the same does not happen for plastic or glass pieces. To overcome this limitation, the use of microwave imaging is proposed in this work. The goal is to develop a microwave system to be used along the production chain. To cope with this challenging scenario, in which the measurement time is reduced and only a limited amount of data is available, an imaging strategy taking advantage of the target's movement and of the expected small size of the sought contamination is developed. In this communication, the rationale of the approach is described and assessed in a simple, yet meaningful case.

The present paper describes our on-going work towards the realization of a novel device to perform continuous monitoring of a patient after a stroke onset. The realization of the antenna array and of the control electronics will be discussed, together with a first experimental test of the system.

This work presents some preliminary results from applying our previously developed microwave imaging algorithm based on two-step iterative shrinkage/thresholding (TwIST) to data measured from an experimental microwave imaging system. Combining the distorted Born iterative method (DBIM) with the TwIST linear solver, our two-dimensional (2-D) algorithm is applied to reconstruct 2-D slices of the complex permittivity of the interrogated imaging domain. Experimental data are obtained by rotating a two-antenna system along the cylindrical imaging domain, which is filled with Triton X-100. The imaging object is an anatomically realistic breast phantom with a tube filled water representing the tumor-like target. Measurements are covered in the frequency range from 0.5 to 4.0 GHz. The paper presents reconstructed images at 900 MHz, while more results will be presented at the conference.

In this work we present an experimental study of qualitative microwave imaging algorithms for breast cancer detection. All the experiments are carried out with a 3-D printed realistic breast phantom filled with designed tissue mimicking liquids. In the following, the first experimental results using the Truncated Singular Value Decomposition (TSVD) scheme and the Linear Sampling Method (LSM) reconstructions are reported.

In this paper we describe the experimental testing of our microwave imaging (MWI) system prototype for use in research towards early breast cancer detection. The main characteristics of the proposed MWI prototype are the low cost and the portability due to the use, for signals generation and acquisition, of low-cost yet high-precision off-the-shelf components (COTS) that replace a costly vector network analyzer. Good detections are reported for simple breast phantoms.

In this paper a microwave imaging system for use in research towards early breast cancer detection is presented. In the proposed system signals generation and acquisition are performed with low-cost yet high-precision off-the-shelf components to replace the vector network analyzer. Experimental detection results are reported.

In this paper we presents experimental results of a designed microwave-imaging system prototype combined with the interferometric multiple signal classification (I-MUSIC) algorithm for use in research towards early breast cancer detection.

A method to efficiently apply Domain-Decomposition (DD) to the MoM via the Synthetic Function eXpansion (SFX) is presented. Special emphasis is placed on the automatic generation of block subdivision of an arbitrary structure, which is key for all DD approaches. The DD-SFX approach is integrated within an FFT-based fast solver. Numerical experiments are presented in order to validate the method.

The demand for personalized and non-invasive technologies for diagnostics of brain-related diseases is a challenge involving multiple research fields. In this context, emerging electromagnetic (EM) techniques are receiving increased attention [1] . Among these techniques, microwave imaging (MWI) has the potential to address specific clinical needs such as intra-cerebral hemorrhage (ICH) detection and monitoring. The success of an MWI brain scanner is strongly dependent on its hardware characteristics. For instance, to achieve a device capable of detecting a hemorrhage inside the brain, array of antennas immersed into a coupling medium are typically used to transmit microwaves in the 0.5–1.5 GHz frequency range into the brain tissue and receive the resulting scattered signal [2] . In addition, our previous studies have shown that metasurface (MTS) structures can be used to enhance transmission and couple the incident power into the region of interest [3] .

International audience; This paper presents the design of the layout of the radiating part of a microwave imaging system for brain stroke monitoring. The radiating part of the system is constituted by an array of antennas placed tangent to a surface conformal to the upper part of head and the design procedure addresses the positioning and the number of the array elements. To this end, an analysis of the relevant scattering operator is performed, taking into account the limited dynamic of the measurement system and the limited number of implemented antennas. Finally, a preliminary tomographic image of a hemorrhagic stroke obtained with synthetic data is reported.