Search Results (27)

Here, we propose an analytical approach to simulating MammoWave, a novel apparatus for breast cancer detection using microwave imaging. The approach is built upon the theory of cylindrical waves emitted by line sources. The sample is modelled as a cylinder with an inclusion. Our results indicate that when compared with phantom measurements, our approach gives an average relative error (between the image generated through measurement with phantoms and the image generated through the analytical simulation approach) of less than 6% when considering the full frequency band of 1–9 GHz. The procedure permits the simulation of the MammoWave imaging system loaded with multilayered eccentric cylinders; thus, it can be used to obtain an insight into MammoWave’s detection capability, without having to perform either time-consuming full-wave simulations or phantom measurements. Full article

This paper demonstrates the design steps of a slot-loaded Vivaldi antenna for biomedical microwave imaging applications, showing the influence of the design parameters on the antenna’s dimensions and performances. Several antenna miniaturization techniques were taken into consideration during the design: reduction in the electromagnetic wavelength by using a high-permittivity substrate material (relative permittivity ${ϵ}_r=10.2$), the placement of the antenna inside a coupling medium (${ϵ}_r=23$), and the elongation of the current path by etching slots on each side of the radiator to reduce the antenna’s lowest resonant frequency without increasing its physical dimensions. Moreover, an analysis of different antenna slot design scenarios was performed considering different slot lengths, inclination angles, positions, and numbers. Considering the frequency range of microwave imaging (i.e., about 500 MHz–5 GHz) and the array arrangement typical of microwave imaging, the best design was chosen. Finally, the antenna was fabricated and its performances in the coupling medium were characterized. The simulation and measurement results showed good agreement between each other. In comparison with literature antennas, the one developed in this work shows wide bandwidth and compact dimensions. Full article

The memristor, a revolutionary electronic component, mimics both neural synapses and electromagnetic induction phenomena. Recent study challenges are the development of effective neural models and discovering their dynamics. In this study, we propose a novel Hopfield neural network model leveraging multistable memristors, showcasing its efficacy in encoding biomedical images. We investigate the equilibrium states and dynamic behaviors of our designed model through comprehensive numerical simulations, revealing a rich array of phenomena including periodic orbits, chaotic dynamics, and homogeneous coexisting attractors. The practical realization of our model is achieved using a microcontroller, with experimental results demonstrating strong agreement with theoretical analyses. Furthermore, harnessing the chaos inherent in the neural network, we develop a robust biomedical image encryption technique, validated through rigorous computational performance tests. Full article

Terahertz (THz) waves are electromagnetic waves in the 0.1 to 10 THz frequency range, and THz imaging is utilized in a range of applications, including security inspections, biomedical fields, and the non-destructive examination of materials. However, THz images have a low resolution due to the long wavelength of THz waves. Therefore, improving the resolution of THz images is a current hot research topic. We propose a novel network architecture called J-Net, which is an improved version of U-Net, to achieve THz image super-resolution. It employs simple baseline blocks which can extract low-resolution (LR) image features and learn the mapping of LR images to high-resolution (HR) images efficiently. All training was conducted using the DIV2K+Flickr2K dataset, and we employed the peak signal-to-noise ratio (PSNR) for quantitative comparison. In our comparisons with other THz image super-resolution methods, J-Net achieved a PSNR of 32.52 dB, surpassing other techniques by more than 1 dB. J-Net also demonstrates superior performance on real THz images compared to other methods. Experiments show that the proposed J-Net achieves a better PSNR and visual improvement compared with other THz image super-resolution methods. Full article

Breath is one of the most important physiological features of human life. In particular, it is significant to monitor the physical characteristics of breath, such as breath frequency and tidal volume. Breath sensors play an important role in the field of human health monitoring. However, an electronic breath sensor is not stable or even safe when the patient is in a Magnetic Resonance Imaging (MRI) system or during any oncology treatment that requires radiation and other high electric/magnetic fields. Fiber-optic-based sensors have attracted a considerable amount of attention from researchers since they are immune to electromagnetic interference. Here, we propose and demonstrate a fiber-optic-based relative-humidity (RH)-sensing strategy by depositing Ti₃C₂T_x nanosheets onto an etched single-mode fiber (ESMF). The humidity sensor function is realized by modulating the transmitted light in the ESMF using the excellent hydrophilic properties of Ti₃C₂T_x. Experiments show that the coated Ti₃C₂T_x nanosheets can effectively modulate the transmitted light in the ESMF in the relative humidity range of 30~80% RH. The sensor’s fast response time of 0.176 s and recovery time of 0.521 s allow it to be suitable for real-time human breath monitoring. The effective recognition of different breath rhythms, including fast, normal, deep, and strong breathing patterns, has been realized. This work demonstrates an all-optical Ti₃C₂T_x-based sensing platform that combines Ti₃C₂T_x with an optical fiber for humidity sensing for the first time, which has great promise for breath monitoring and presents novel options for gas-monitoring applications in the biomedical and chemical fields. Full article

In this paper, a deep learning technique for tumor detection in a microwave tomography framework is proposed. Providing an easy and effective imaging technique for breast cancer detection is one of the main focuses for biomedical researchers. Recently, microwave tomography gained a great attention due to its ability to reconstruct the electric properties maps of the inner breast tissues, exploiting nonionizing radiations. A major drawback of tomographic approaches is related to the inversion algorithms, since the problem at hand is nonlinear and ill-posed. In recent decades, numerous studies focused on image reconstruction techniques, in same cases exploiting deep learning. In this study, deep learning is exploited to provide information about the presence of tumors based on tomographic measures. The proposed approach has been tested with a simulated database showing interesting performances, in particular for scenarios where the tumor mass is particularly small. In these cases, conventional reconstruction techniques fail in identifying the presence of suspicious tissues, while our approach correctly identifies these profiles as potentially pathological. Therefore, the proposed method can be exploited for early diagnosis purposes, where the mass to be detected can be particularly small. Full article

The purpose of this paper is to provide an in-depth review of plasmonic metal nanoparticles made from rhodium, platinum, gold, or silver. We describe fundamental concepts, synthesis methods, and optical sensing applications of these nanoparticles. Plasmonic metal nanoparticles have received a lot of interest due to various applications, such as optical sensors, single-molecule detection, single-cell detection, pathogen detection, environmental contaminant monitoring, cancer diagnostics, biomedicine, and food and health safety monitoring. They provide a promising platform for highly sensitive detection of various analytes. Due to strongly localized optical fields in the hot-spot region near metal nanoparticles, they have the potential for plasmon-enhanced optical sensing applications, including metal-enhanced fluorescence (MEF), surface-enhanced Raman scattering (SERS), and biomedical imaging. We explain the plasmonic enhancement through electromagnetic theory and confirm it with finite-difference time-domain numerical simulations. Moreover, we examine how the localized surface plasmon resonance effects of gold and silver nanoparticles have been utilized for the detection and biosensing of various analytes. Specifically, we discuss the syntheses and applications of rhodium and platinum nanoparticles for the UV plasmonics such as UV-MEF and UV-SERS. Finally, we provide an overview of chemical, physical, and green methods for synthesizing these nanoparticles. We hope that this paper will promote further interest in the optical sensing applications of plasmonic metal nanoparticles in the UV and visible ranges. Full article

Microwaves are non-ionizing electromagnetic radiation with waves of electrical and magnetic energy transmitted at different frequencies. They are widely used in various industries, including the food industry, telecommunications, weather forecasting, and in the field of medicine. Microwave applications in medicine are relatively a new field of growing interest, with a significant trend in healthcare research and development. The first application of microwaves in medicine dates to the 1980s in the treatment of cancer via ablation therapy; since then, their applications have been expanded. Significant advances have been made in reconstructing microwave data for imaging and sensing applications in the field of healthcare. Artificial intelligence (AI)-enabled microwave systems can be developed to augment healthcare, including clinical decision making, guiding treatment, and increasing resource-efficient facilities. An overview of recent developments in several areas of microwave applications in medicine, namely microwave imaging, dielectric spectroscopy for tissue classification, molecular diagnostics, telemetry, biohazard waste management, diagnostic pathology, biomedical sensor design, drug delivery, ablation treatment, and radiometry, are summarized. In this contribution, we outline the current literature regarding microwave applications and trends across the medical industry and how it sets a platform for creating AI-based microwave solutions for future advancements from both clinical and technical aspects to enhance patient care. Full article

Today, MXenes and their composites have shown attractive capabilities in numerous fields of electronics, co-catalysis/photocatalysis, sensing/imaging, batteries/supercapacitors, electromagnetic interference (EMI) shielding, tissue engineering/regenerative medicine, drug delivery, cancer theranostics, and soft robotics. In this aspect, MXene-carbon nanotube (CNT) composites have been widely constructed with improved environmental stability, excellent electrical conductivity, and robust mechanical properties, providing great opportunities for designing modern and intelligent systems with diagnostic/therapeutic, electronic, and environmental applications. MXenes with unique architectures, large specific surface areas, ease of functionalization, and high electrical conductivity have been employed for hybridization with CNTs with superb heat conductivity, electrical conductivity, and fascinating mechanical features. However, most of the studies have centered around their electronic, EMI shielding, catalytic, and sensing applications; thus, the need for research on biomedical and diagnostic/therapeutic applications of these materials ought to be given more attention. The photothermal conversion efficiency, selectivity/sensitivity, environmental stability/recyclability, biocompatibility/toxicity, long-term biosafety, stimuli-responsiveness features, and clinical translation studies are among the most crucial research aspects that still need to be comprehensively investigated. Although limited explorations have focused on MXene-CNT composites, future studies should be planned on the optimization of reaction/synthesis conditions, surface functionalization, and toxicological evaluations. Herein, most recent advancements pertaining to the applications of MXene-CNT composites in sensing, catalysis, supercapacitors/batteries, EMI shielding, water treatment/pollutants removal are highlighted, focusing on current trends, challenges, and future outlooks. Full article

Manganese-zinc ferrite (MZF) is known as high-performance magnetic material and has been used in many fields and development. In the biomedical applications, the biocompatible MZF formulation attracted much attention. In this study, water-soluble amphiphilic vitamin E (TPGS, d-alpha-tocopheryl poly(ethylene glycol 1000) succinate) formulated MZF nanoparticles were synthesized to serve as both a magnetic resonance imaging (MRI) contrast agent and a vehicle for creating magnetically induced hyperthermia against cancer. The MZF nanoparticles were synthesized from a metallic acetylacetonate in an organic phase and further modified with TPGS using an emulsion and solvent-evaporation method. The resulting TPGS-modified MZF nanoparticles exhibited a dual-contrast ability, with a longitudinal relaxivity (35.22 s⁻¹ mM Fe⁻¹) and transverse relaxivity (237.94 s⁻¹ mM Fe⁻¹) that were both higher than Resovist^®. Furthermore, the TPGS-assisted MZF formulation can be used for hyperthermia treatment to successfully suppress cell viability and tumor growth after applying an alternating current (AC) electromagnetic field at lower amplitude. Thus, the TPGS-assisted MZF theranostics can not only be applied as a potential contrast agent for MRI but also has potential for use in hyperthermia treatments. Full article

Magnetoplasmonics based on composite nanostructures is widely used in many biomedical applications. Nanostructures, consisting of a magnetic core and a gold shell, exhibit plasmonic properties, that allow the concentration of electromagnetic energy in ultra-small volumes when used, for example, in imaging and therapy. Magnetoplasmonic nanostructures have become an indispensable tool in nanomedicine. The gold shell protects the core from oxidation and corrosion, providing a biocompatible platform for tumor imaging and cancer treatment. By adjusting the size of the core and the shell thickness, the maximum energy concentration can be shifted from the ultraviolet to the near infrared, where the depth of light penetration is maximum due to low scattering and absorption by tissues. A decrease in the thickness of the gold shell to several nanometers leads to the appearance of the quantum effect of spatial dispersion in the metal. The presence of the quantum effect can cause both a significant decrease in the level of energy concentration by plasmon particles and a shift of the maxima to the short-wavelength region, thereby reducing the expected therapeutic effect. In this study, to describe the influence of the quantum effect of spatial dispersion, we used the discrete sources method, which incorporates the generalized non-local optical response theory. This approach made it possible to account for the influence of the nonlocal effect on the optical properties of composite nanoparticles, including the impact of the asymmetry of the core-shell structure on the energy characteristics. It was found that taking spatial dispersion into account leads to a decrease in the maximum value of the concentration of electromagnetic energy up to 25%, while the blue shift can reach 15 nm. Full article

In this paper, a unique approach to the imaging of non-metallic media using capacitive sensing is presented. By using customized sensor plates in single-ended and differential configurations, responses to hidden objects can be captured over a cylindrical aperture surrounding the inspected medium. Then, by processing the acquired data using a novel imaging technique based on the convolution theory, Fourier and inverse Fourier transforms, and exact low resolution electromagnetic tomography (eLORETA), images are reconstructed over multiple radial depths using the acquired sensor data. Imaging hidden objects over multiple depths has wide range of applications, from biomedical imaging to nondestructive testing of the materials. Performance of the proposed imaging technique is demonstrated via experimental results. Full article

Magnetic induction tomography (MIT) is a contactless, low-energy method used to visualize the conductivity distribution inside a body under examination. A particularly demanding task is the three-dimensional (3D) imaging of voluminous bodies in the biomedical impedance regime. While successful MIT simulations have been reported for this regime, practical demonstration over the entire depth of weakly conductive bodies is technically difficult and has not yet been reported, particularly in terms of more realistic requirements. Poor sensitivity in the central regions critically affects the measurements. However, a recently simulated MIT scanner with a sinusoidal excitation field topology promises improved sensitivity (>20 dB) from the interior. On this basis, a large and fast 3D MIT scanner was practically realized in this study. Close agreement between theoretical forward calculations and experimental measurements underline the technical performance of the sensor system, and the previously only simulated progress is hereby confirmed. This allows 3D reconstructions from practical measurements to be presented over the entire depth of a voluminous body phantom with tissue-like conductivity and dimensions similar to a human torso. This feasibility demonstration takes MIT a step further toward the quick 3D mapping of a low conductive and voluminous object, for example, for rapid, harmless and contactless thorax or lung diagnostics. Full article

The interaction of an external magnetic field with magnetic objects affects their response and is a fundamental property for many biomedical applications, including magnetic resonance and particle imaging, electromagnetic hyperthermia, and magnetic targeting and separation. Magnetic alignment and relaxation are widely studied in the context of these applications. In this study, we theoretically investigate the alignment dynamics of a rotational magnetic particle as an inverse process to Brownian relaxation. The selected external magnetic flux density ranges from $5\mathsf{\mu }\mathrm{T}$ to $5\mathrm{T}$. We found that the viscous torque for arbitrary rotating particles with a history term due to the inertia and friction of the surrounding ambient water has a significant effect in strong magnetic fields (range 1–$5\mathrm{T}$). In this range, oscillatory behavior due to the inertial torque of the particle also occurs, and the stochastic Brownian torque diminishes. In contrast, for weak fields (range 5–$50\mathsf{\mu }\mathrm{T}$), the history term of the viscous torque and the inertial torque can be neglected, and the stochastic Brownian torque induced by random collisions of the surrounding fluid molecules becomes dominant. These results contribute to a better understanding of the molecular mechanisms of magnetic particle alignment in external magnetic fields and have important implications in a variety of biomedical applications. Full article

This paper presents a review on the biomedical applications of electromagnetic detection in recent years. First of all, the thermal, non-thermal, and cumulative thermal effects of electromagnetic field on organism and their biological mechanisms are introduced. According to the electromagnetic biological theory, the main parameters affecting electromagnetic biological effects are frequency and intensity. This review subsequently makes a brief review about the related biomedical application of electromagnetic detection and biosensors using frequency as a clue, such as health monitoring, food preservation, and disease treatment. In addition, electromagnetic detection in combination with machine learning (ML) technology has been used in clinical diagnosis because of its powerful feature extraction capabilities. Therefore, the relevant research involving the application of ML technology to electromagnetic medical images are summarized. Finally, the future development to electromagnetic detection for biomedical applications are presented. Full article