This paper presents the design of a novel lowcomplexity microwave imaging system for monitoring brain stroke. In particular, the design is concerned with the determination of the optimal layout of the antennas array, namely minimum number, positions and polarization of the radiating elements, enabling the acquisition of an amount of data such to assure a reliable imaging. This goal is achieved by adopting a rigorous design procedure based on the inspection of the singular value decomposition of the relevant discretized scattering operator and taking into account the actual dynamics and signal to noise ratio of the measurement system. The design is first carried out in the case of ideal dipoles and then extended and assessed for actual printed monopole antennas, developed for the imaging system. The resulting system is a helmet equipped with 24 antennas, whose performances have been numerically validated in terms of both spatial resolution and reconstruction capabilities, by employing full-wave numerical simulations, realistic 3-D phantoms of the human head and an accurate modeling of the actual antennas employed in the system.

This work focuses on brain stroke imaging via microwave technology. In particular, the open issue of monitoring patients after stroke onset is addressed here in order to provide clinicians with a tool to control the effectiveness of administered therapies during the follow-up period. In this paper, a novel prototype is presented and characterized. The device is based on a low-complexity architecture which makes use of a minimum number of properly positioned and designed antennas placed on a helmet. It exploits a differential imaging approach and provides 3D images of the stroke. Preliminary experiments involving a 3D phantom filled with brain tissue-mimicking liquid confirm the potential of the technology in imaging a spherical target mimicking a stroke of a radius equal to 1.25 cm.

Microwaves can safely and non-destructively illuminate and penetrate dielectric materials, making them an attractive solution for various medical tasks, including detection, diagnosis, classification, and monitoring. Their inherent electromagnetic properties, portability, cost-effectiveness, and the growth in computing capabilities have encouraged the development of numerous microwave sensing and imaging systems in the medical field, with the potential to complement or even replace current gold-standard methods. This review aims to provide a comprehensive update on the latest advances in medical applications of microwaves, particularly focusing on the near-field ones working within the 1–15 GHz frequency range. It specifically examines significant strides in the development of clinical devices for brain stroke diagnosis and classification, breast cancer screening, and continuous blood glucose monitoring. The technical implementation and algorithmic aspects of prototypes and devices are discussed in detail, including the transceiver systems, radiating elements (such as antennas and sensors), and the imaging algorithms. Additionally, it provides an overview of other promising cutting-edge microwave medical applications, such as knee injuries and colon polyps detection, torso scanning and image-based monitoring of thermal therapy intervention. Finally, the review discusses the challenges of achieving clinical engagement with microwave-based technologies and explores future perspectives.

This paper presents the experimental validation of a microwave imaging system for real-time monitoring of brain stroke in the post-acute stage. The system exploits a low-complexity sensing apparatus and a multi-frequency microwave imaging algorithm with a novel artifact removal feature. Phantoms of a homogeneous anthropomorphic head and an ellipsoidal non-static stroke mimicking target, varying gradually from 0 cm ³ to 60 cm ³ , are employed for the experiments. The phantom and the evolving target are filled with appropriate alcohol-based mixtures to mimic the different dielectric properties of the relevant tissue. The microwave imaging scanner operates using a 22-antennas architecture formed by printed flexible antennas with a custom-made matching medium. The system provides 3-D images of the entire brain region, exploiting differential multi-view scattering measures and the distorted Born approximation to build a pre-computed imaging kernel. The results show the system’s capability to follow up the continuous progression of hemorrhage and ischemia zones with centimetric spatial resolution and to provide information on whether the stroke is growing or shrinking.

We present a domain decomposition (DD) framework for the analysis of impenetrable structures; it allows for the electric field integral equation (EFIE) and combined field integral equation (CFIE), and for open, closed, and open-closed structures. The DD results in an effective preconditioner for large and complex problems exploiting iterative solution and fast factorizations. The DD employs specialized transmission conditions among the domains, and the use of discontinuous Galerkin (DG) allows conformal as well as nonconformal discretizations of domain boundaries; the nonconformal nature of the decomposition gives considerable flexibility in the meshing. The strategy is highly parallelizable, as all the operations involving the subdomains can be performed in parallel. The proposed scheme is implementation independent and can be easily merged with existing electromagnetic codes.

Microwave imaging is an emerging breast cancer diagnostic technique, which aims at complementing already established methods like mammography, magnetic resonance imaging, and ultrasound. It offers two striking advantages: no-risk for the patient and potential low-cost for national health systems. So far, however, the prototypes developed for validation in labs and clinics used costly lab instruments such as a vector network analyzer (VNA). Moreover, the CPU time required by complex image reconstruction algorithms may not be compatible with the duration of a medical examination. In this paper, both these issues are tackled. Indeed, we present a prototype system based on low-cost and off-the-shelf microwave components, custom-made antennas, and a small form-factor processing system with an embedded field-programmable gate array for accelerating the execution of the imaging algorithm. We show that our low-cost system can compete with an expensive VNA in terms of accuracy, and it is more than 20x faster than a high-performance server at image reconstruction.