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Magnetic Resonance imaging based Electrical Properties Tomography (MR-EPT) is a non-invasive technique that measures the electrical properties (EPs) of biological tissues. In this work, we present and numerically investigate the performance of an unrolled, physics-assisted method for 2D MR-EPT reconstructions, where a cascade of Convolutional Neural Networks is used to compute the contrast update. Each network takes in input the EPs and the gradient descent direction (encoding the physics underlying the adopted scattering model) and returns as output the updated contrast function. The network is trained and tested in silico using 2D slices of realistic brain models at 128 MHz. Results show the capability of the proposed procedure to reconstruct EPs maps with quality comparable to that of the popular Contrast Source Inversion-EPT, while significantly reducing the computational time.

The canonical problem of designing the complex excitations feeding an array such to ensure a desired field intensity distribution inside a given region of interest, while keeping it under control in some other regions, is addressed. To this end, an auxiliary physics inspired model for the induced total field is proposed, whose off-line analysis allows a simplified approach to understand the convenient and non-convenient field interferences between canonical solutions for the induced total field, that are zero order Bessel functions. Moreover, its analysis drastically reduces the computational burden associated to the multi-control points based approaches. The problem at hand plays a key role in many different applications, including radio communications, wireless power transfer as well as hyperthermia treatment planning, and in this paper attention is paid to radiofrequency shimming in magnetic resonance imaging. In fact, the proposed model and tools are tailored to the challenging case of leveling of the magnetic field intensity within an MRI scanner and in case of a bidimensional realistic head phantom.

Quantitative microwave imaging employing an ideal Veselago lens is demonstrated using synthetic 2D experiments. Reconstructions of the complex-valued dielectric constant of an arbitrary object-of-interest are obtained from noiseless data using a non-iterative technique. A closed-form Veselago lens Green’s function is utilized in the formulation of the problem. The contrast sources corresponding to a single illumination of the object-of-interest is recovered using total-field measurements at several receiver points located in the lens’ focusing region. Collecting the field in the presence of the ideal Veselago lens produces well-conditioned matrices for the discretized inverse source problem. The contrast is then directly obtained by first calculating the total-field within the object. Synthetic examples having features as small as $\lambda /25$ show that the resolution is only limited by the signal-to-noise ratio of data. Experiments with noisy data reveals that the inversion procedure directly mirrors the noise in the data. Two new filtering processes are introduced based on the truncated Singular Value Decomposition of the data operator and the domain operator involved in the inversion process. These successfully deal with noisy reconstructions. Results show that using the new filtering methods, even with a single illuminating source, outperforms the least-squares method with several illuminating sources.

Non-linearity arising from mutual interactions is one of the two main difficulties to be addressed in inverse scattering. In this paper, we first review and describe under a common rationale some approaches which have been introduced in literature in order to counteract non-linearity. In particular, we focus on possible rewritings of the Lippman Schwinger basic equation such to reduce the `degree of non-linearity' of inverse scattering problem. In detail, three different rewritings are discussed and compared by emphasizing similarities and differences, and in the same `rewriting' spirit, we also summarize and discuss the `Virtual Experiments' framework. Then, some possible and effective joint exploitations of the above concepts are introduced, discussed and tested against numerical examples.

Ground-penetrating radar (GPR) technology for underground exploration consists of the transmission of an electromagnetic signal in the ground for sensing the presence of buried objects. While monostatic or bistatic configurations are usually adopted, a limited number of multistatic GPR systems have been proposed in the scientific literature. In this article, we investigate the recovery performance of a specific and unconventional contactless multistatic GPR system, designed at the Georgia Institute of Technology for the subsurface imaging of antitank and antipersonnel plastic mines. In particular, for the first time, tomographic approaches are tested against this experimental multistatic GPR system, while most GPR processing in the scientific literature processes multimonostatic experimental data sets. First, by mimicking the system at hand, an accurate theoretical as well as numerical analysis is performed in order to estimate the data information content and the performance achievable. Two different tomographic linear approaches are adopted, i.e., the linear sampling method and the Born approximation (BA) method, this latter enhanced by means of the compressive sensing (CS) theoretical framework. Then, the experimental data provided by the Georgia Institute of Technology are processed by means of a multifrequency CS- and BA-based method, thus generating very accurate 3D maps of the investigated underground scenario.

A novel approach to the design of cloaking devices is presented which takes inspiration from the Fourier diffraction theorem. In particular, we first put on a common basis different linear approximations of the scattering equations. Then, a very simple procedure to get invisibility (under the given approximation at hand) is proposed. The approach is assessed through numerical examples concerning 3-D non-canonical objects.

Purpose: Hyperthermia treatment quality determines treatment effectiveness as shown by the clinically derived thermal-dose effect relations. SAR based optimization factors are used as possible surrogate for temperature, since they are not affected by thermal tissue properties uncertainty and variations. Previously, target coverage (TC) at the 25% and 50% iso-SAR level was shown predictive for treatment outcome in superficial hyperthermia and the target-to-hot-spot-quotient (THQ) was shown to highly correlate with predictive temperature in deep pelvic hyperthermia. Here, we investigate the correlation with temperature for THQ and TC using an ‘intermediate’ scenario: semi-deep hyperthermia in the head & neck region using the HYPERcollar3D. Methods: Fifteen patient-specific models and two different planning approaches were used, including random perturbations to circumvent optimization bias. The predicted SAR indicators were compared to predicted target temperature distribution indicators T50 and T90, i.e., the median and 90th percentile temperature respectively. Results: The intra-patient analysis identified THQ, TC25 and TC50 as good temperature surrogates: with a mean correlation coefficient R2T50 = 0.72 and R2T90=0.66. The inter-patient analysis identified the highest correlation with TC25 (R2T50 = 0.76, R2T90=0.54) and TC50 (R2T50 = 0.74, R2T90 = 0.56). Conclusion: Our investigation confirmed the validity of our current strategy for deep hyperthermia in the head & neck based on a combination of THQ and TC25. TC50 was identified as the best surrogate since it enables optimization and patient inclusion decision making using one single parameter.

At the local scale, environmental parameters often require monitoring by means of affordable measuring techniques and technologies given they need to be frequently surveyed. Streamflow in riverbeds or in channels is a hydrological variable that needs to be monitored in order to keep the runoff regimes under control and somehow forecast floods, allowing prevention of damage for people and infrastructure. Moreover, measuring such a variable is always extremely important for the knowledge of the environmental status of connected aquatic ecosystems. This paper presents a new approach to assessing hydrodynamic features related to a given channel by means of a beamforming technique that was applied to video sensing. Different features have been estimated, namely the flow velocity, the temperature, and the riverbed movements. The applied beamforming technique works on a modified sum and delay method, also using the Multiple Signal Classification algorithm (MUSIC), by acting as Synthetic Aperture Radar (SAR) post-processing. The results are very interesting, especially compared to the on-site measured data and encourage the use of affordable video sensors located along the channel or river course for monitoring purposes. The paper also illustrates the use of beamforming measurements to be calibrated by means of conventional techniques with more accurate data. Certainly, the results can be improved; however, they indicate some margins of improvements and updates. As metrics of assessment, a histogram of greyscale/pixels was adopted, taking into account the example of layers and curve plots. They show changes according to the locations where the supporting videos were obtained.

Theoretical predictions as well as experiments performed at storage rings have shown that the lifetimes of β-radionuclides can change significantly as a function of the ionization state. In this paper we describe an innovative approach, based on the use of a compact plasma trap to emulate selected stellar-like conditions. It has been proposed within the PANDORA project (Plasmas for Astrophysics, Nuclear Decay Observation and Radiation for Archaeometry) with the aim to measure, for the first time in plasma, nuclear β-decay rates of radionuclides involved in nuclear-astrophysics processes. To achieve this task, a compact magnetic plasma trap has been designed to reach the needed plasma densities, temperatures, and charge-states distributions. A multi-diagnostic setup will monitor, on-line, the plasma parameters, which will be correlated with the decay rate of the radionuclides. The latter will be measured through the detection of the γ-rays emitted by the excited daughter nuclei following the β-decay. An array of 14 HPGe detectors placed around the trap will be used to detect the emitted γ-rays. For the first experimental campaign three isotopes, 176Lu, 134Cs, and 94Nb, were selected as possible physics cases. The newly designed plasma trap will also represent a tool of choice to measure the plasma opacities in a broad spectrum of plasma conditions, experimentally poorly known but that have a great impact on the energy transport and spectroscopic observations of many astrophysical objects. Status and perspectives of the project will be highlighted in the paper.

An experimental study is carried out to assess the effect of temperature on the conversion efficiency of ultrahigh-frequency energy harvesters based on diode-capacitor Dickson charge pumps, frequently used in self-energizing circuits, such as in radio frequency identification tags or in wireless sensor nodes. Using off-the-shelf Schottky diodes often adopted for this application, it is shown that the harvester conversion efficiency at 868 MHz is temperature dependent due to the changing rectification ratio, namely the ratio between the forward and the reverse current flowing through the low barrier height Schottky diodes, which both show a positive derivative with T. The experimental study, supported by SPICE simulations, has shown that a temperature variation might be particularly harmful at the lowest incident power regimes, when even a minimal drop in the conversion efficiency might determine the out-of-servicing of a wirelessly energized circuit.

Abstract The synthesis of non-magnetic 2D dielectric cloaks as proper solutions of an inverse scattering problem is addressed in this paper. Adopting the relevant integral formulation governing the scattering phenomena, analytic and numerical approaches are exploited to provide new insights on how frequency and direction of arrival of the incoming wave may influence the cloaking mechanism in terms of permittivity distribution within the cover region. In quasi-static (subwavelength) regime a solution is analytically derived in terms of homogeneous artificial dielectric cover with ε ε 0 able to hide the object for a given number of directions of the incident field. Simulated results confirm the validity of both analytic and numerical methodologies and allow to estimate effective bandwidths both in terms of frequency range and direction of arrival of the impinging field.

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.

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.

The estimation of electrical properties of living biological tissues is relevant to several medical applications ranging from hyperthermia treatment planning to dosimetry and, more in general, is pivotal for a fundamental understanding of bioelectromagnetic interactions. Non-invasive electromagnetic imaging, either based on the processing of electric fields measured via microwave tomography or magnetic fields acquired in magnetic resonance is suitable to pursue this goal. In this framework, the possibility of imaging without the need of phase information would be extremely relevant, as it would enable simpler and more reliable devices and would avoid limiting assumptions typically used in the literature. With reference to the canonical yet significant 2D case, in this paper we propose an inverse scattering approach for tissue characterization from only-amplitude electromagnetic data, which, by virtue of a unified mathematical framework, is viable for both microwave tomography and magnetic resonance imaging. The key feature of the method is the innovative use of morphological maps derived by other medical imaging modalities as prior spatial information. In particular, these images are exploited to define a convenient and effective patient-specific representation of the unknowns. The approach is tested against simulated data derived from anatomically realistic scenarios. [ABSTRACT FROM AUTHOR]