Search Results (189)

Unmanned aerial vehicle (UAV) applications are growing fast in different sectors, such as agricultural, commercial, academic, leisure, and health fields. However, drones pose a significant threat to public safety due to their ability to transmit information, particularly when used in an unauthorized or malicious manner. In fact, in order to protect citizens’ privacy and prevent accidents in high-traffic areas due to poorly controlled flights, no-fly zones for drones have been established in the legislation of a number of countries. Most common UAV detection techniques are based on radio frequencies, which identify drones and their models by monitoring radio frequency signals. However, differentiating between multiple UAVs of the same model is their main limitation. This article fills this gap by proposing a method for physically tracking the communication frames of a registered UAV in the presence of another UAV of the same model. A measurement campaign was conducted to collect real-world RF communication signals from two DJI MAVIC 2 Zoom, two DJI Air2S, and two DJI Phantom drones. This measurement was performed inside and outside an anechoic chamber in order to study the UAV’s communication without any interference and in the presence of other communications. Through detailed statistical analysis, we characterized features such as communication duration, time intervals between communications, signal strength, and patterns in communication timing sequences. Our analysis revealed unique, identifiable patterns for each UAV, even within identical models. Based on these results, we developed an automated system that links communication frames to the corresponding registered drones. The proposed method fills gaps in drone detection and surveillance models, providing valuable information for applications in the fields of security and airspace management. This research lays the foundation for drone identification solutions, thereby addressing a major limitation of current detection technologies. Full article

Background: Arterial stenosis produces nonlinear changes in vascular impedance that are challenging to investigate in real time using either benchtop flow phantoms or high-fidelity computational fluid dynamics (CFD) models. Objective: This study aimed to develop and evaluate a low-cost printed circuit board (PCB) analog capable of reproducing the hemodynamic effects of progressive arterial stenosis through an R–L–C mapping of vascular mechanics. Methods: A lumped-parameter (0D) electrical network was constructed in which voltage represented pressure, current represented flow, resistance modeled viscous losses, capacitance corresponded to vessel compliance, and inductance represented fluid inertance. A variable resistor simulated focal stenosis and was adjusted incrementally to represent progressive narrowing. Input U_in, output U_out, peak-to-peak V_pp, and mean V_avg voltages were recorded at a driving frequency of 50 Hz. Physiological correspondence was established using the canonical relationships. $R={\displaystyle \frac{8\mu l}{\pi r^4}}$, $L={\displaystyle \frac{pl}{\pi r^2}}$, $C={\displaystyle \frac{3\pi r^3}{2Eh}}$, where μ is blood viscosity, ρ is density, E is Young’s modulus, and h is wall thickness. A calibration constant was applied to convert measured voltage differences into pressure differences. Results: As simulated stenosis increased, the circuit exhibited a monotonic rise in U_out and V_pp, with a precise inflection beyond mid-range narrowing—consistent with the nonlinear growth in pressure loss predicted by fluid dynamic theory. Replicate measurements yielded stable, repeatable traces with no outliers under nominal test conditions. Qualitative trends matched those of surrogate 0D and CFD analyses, showing minimal changes for mild narrowing (≤25%) and a sharp increase in pressure loss for moderate to severe stenoses (≥50%). The PCB analog uses a simplified, lumped-parameter representation driven by a fixed-frequency sinusoidal excitation and therefore does not reproduce fully characterized physiological systolic–diastolic waveforms or heart–arterial coupling. In addition, the present configuration is intended for relatively straight peripheral arterial segments and is not designed to capture the complex geometry and branching of specialized vascular beds (e.g., intracranial circulation) or strongly curved elastic vessels (e.g., the thoracic aorta). Conclusions: The PCB analog successfully reproduces the characteristic hemodynamic signatures of arterial stenosis in real time and at low cost. The model provides a valuable tool for educational and research applications, offering rapid and intuitive visualization of vascular behavior. Current accuracy reflects assumptions of Newtonian, laminar, and lumped flow; future work will refine calibration, quantify uncertainty, and benchmark results against physiological measurements and full CFD simulations. Full article

The torsional characteristics of human tendons are recognized to have functional and clinical relevance, but are underexplored due to the limited in vivo assessment methods available to measure the dynamic torsion characteristics of a tendon during movement. This study aimed to validate the use of transverse plane ultrasound speckle tracking (ST) for measuring dynamic torsion on silicone phantoms, and to evaluate the capability and reliability of ST in measuring dynamic torsion of the human tibialis posterior tendon (TPT) in vivo. Of the ten silicone phantoms tested in the validation study, ST measurement results strongly correlated with the referencing marker tracking method (R² = 0.81–0.95) and had measurement error similar to or smaller than the hypothesized accuracy of 3° (p > 0.045). Subsequently, when ST was applied to nineteen healthy participants’ TPT in vivo, it was capable of characterizing the dynamic external torsion of the TPT during 0–20° passive foot pronation. Strong correlations were found between the ST-measured angle and the foot pronation angle (R² = 0.98–0.99), and the test–retest reliability was moderate to good (ICC = 0.73–0.87). These findings suggested that ST is a valid and reliable method for measuring dynamic tendon torsion characteristics. Full article

Accurate identification and characterization of subcutaneous tumors are essential for improving breast tumor detection and treatment. This study introduces an innovative Tactile-Sensation Imaging System (TSIS) designed, implemented, and tested to detect and characterize subcutaneous inclusions simulating breast tumors. The system employs a multilayered polydimethylsiloxane (PDMS) optical waveguide that mimics the tactile structure of the human fingertip. By introducing light at a critical angle, the design enables continuous total internal reflection (TIR) within the flexible, transparent waveguide. When external pressure is applied, deformation of the contact area causes light scattering, which is recorded using a high-definition camera and processed as tactile images. Analysis of these images allows estimation of inclusion characteristics such as size, depth, and mechanical properties, including Young’s modulus. Analytical modeling and numerical simulations validated the optical performance of the waveguide, while experimental evaluations using realistic tissue phantoms confirmed the system’s ability to accurately detect and quantify embedded inclusions. The results demonstrated reliable estimations of inclusion dimensions, depths, and stiffness, verifying the system’s sensitivity and precision. The TSIS offers a noninvasive, portable, and cost-efficient solution for quantitative breast tumor assessment, bridging the gap between manual palpation and advanced imaging, with future enhancements aimed at improving resolution and diagnostic accuracy. Full article

This phantom study presents a thorough characterization of the physical image quality of a clinical whole-body photon-counting computed tomography (PCCT) scanner. Multiple quality metrics—noise, noise power spectrum (NPS), task transfer function (TTF), and detectability index (d′)—were analyzed across a range of reconstruction algorithms (filtered back projection, FBP, and Quantum Iterative Reconstruction, QIR, with strength levels Q1–Q4), and varying reconstruction kernels (Br40/Br60/Br76/Br98). Both standard (STD, 0.4 mm slice thickness) and high-resolution (HR, 0.2 mm slice thickness) reconstruction modes were assessed. QIR significantly reduced image noise (60–95%) compared to FBP, particularly with sharper kernels. Spatial resolution improved with increasing QIR strength level for smoother kernels and was further enhanced using HR mode with sharp kernels. HR mode exhibited better noise performance than STD with sharper reconstructions, due to the small pixel effect. While STD mode showed higher d′ values for larger objects, HR mode outperformed it for smaller objects and sharper kernels. Compared to a conventional energy-integrating computed tomography system, the PCCT scanner showed superior d′ values under similar settings. Overall, this study highlights the complex interplay between acquisition and reconstruction parameters on image quality, confirms the potential of PCCT technology, and underscores the need for further clinical validation. Full article

Background: Occlusal dysesthesia (OD), also known as phantom bite syndrome, is characterized by the subjective sensation of an uncomfortable or “wrong” bite despite the absence of objective occlusal pathology. This scoping review aimed to synthesize the current evidence on the epidemiology, etiology, clinical presentation, diagnosis, and management of OD. Methods: The PubMed, Google Scholar, Scopus, Web of Science, ScienceDirect, and Cochrane Library databases were systematically searched using the terms “phantom bite,” “occlusal dysesthesia,” “occlusal hyperawareness,” “occlusal hypervigilance,” “uncomfortable occlusion,” and “oral cenestopathy.” Studies were screened according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria (2020), and evidence quality was assessed using the Oxford Center for Evidence-Based Medicine levels of evidence. Results: A total of 20 studies were included. OD predominantly affected middle-aged women, with symptom durations often exceeding several years, and was believed to be caused by disorderly central sensory processing or maladaptive signal processing rather than by a primary occlusal abnormality, with high rates of psychiatric comorbidities reported. Current evidence supports conservative multidisciplinary management, including patient education, cognitive behavioral therapy, and supportive pharmacotherapy, and irreversible dental interventions are contraindicated. Conclusions: OD is a complex biopsychosocial condition requiring multidisciplinary care. The current low-quality evidence is primarily obtained from case reports and case series. Therefore, high-quality controlled trials are urgently required to establish evidence-based diagnostic criteria and treatment protocols. Full article

Magnetic resonance imaging (MRI) and hyperspectral imaging (HSI) provide complementary information for image-guided neurosurgery, combining high-resolution anatomical detail with tissue-specific optical characterization. This work presents a novel multimodal phantom dataset specifically designed for MRI–HSI integration. The phantoms reproduce a three-layer tissue structure comprising white matter, gray matter, tumor, and superficial blood vessels, using agar-based compositions that mimic MRI contrasts of the rat brain while providing consistent hyperspectral signatures. The dataset includes two designs of phantoms with MRI, HSI, RGB-D, and tracking acquisitions, along with pixel-wise labels and corresponding 3D models, comprising 13 phantoms in total. The dataset facilitates the evaluation of registration, segmentation, and classification algorithms, as well as depth estimation, multimodal fusion, and tracking-to-camera calibration procedures. By providing reproducible, labeled multimodal data, these phantoms reduce the need for animal experiments in preclinical imaging research and serve as a versatile benchmark for MRI–HSI integration and other multimodal imaging studies. Full article

Tissue-mimicking phantoms that accurately replicate human tissue are crucial for validating and optimizing elastography systems and developing new treatment methods. The use of waste-based fibrous structures has the dual benefits of waste reduction and economic viability, mitigating the environmental consequences associated with the textile industry and, thus, posing a particularly interesting avenue of research in today’s ever-more environmentally conscious society. This work explores the development of elastography phantoms through the use of textile waste for sustainable valorization. Two cotton-short fiber-based and two polyester-nonwoven-based phantoms were produced by impregnating these textile structures with animal-origin gelatin. These materials were characterized by scanning electron microscopy (SEM), revealing that the diameter of the waste-based fibers (15.28 ± 6.18–22.40 ± 5.78 μm) falls within the typical size range of scatterers used in acoustic phantoms. It was observed that these fibers provided phantoms with intrinsic acoustic scattering properties, resulting in ultrasound images similar to those obtained in biological tissues. Shear wave elastography (SWE) was used to assess the stiffness of the phantoms, which produced realistic ultrasound images with shear wave speed (SWS) values ranging from 1.87 m s⁻¹ to 8.39 m s⁻¹, closely resembling those in different anatomical structures. This research presents an innovative methodology for producing low-cost and sustainable tissue-mimicking materials, underscoring the potential of textile industry waste for phantom production. Full article

Background: Mock circulatory loops (MCLs) are benchtop experimental platforms that reproduce key features of the human cardiovascular system, providing a safe, controlled, and reproducible environment for haemodynamic investigation. This scoping review aims to systematically map the current landscape of MCLs used for aortic simulation and identify major areas of application. Methods: A systematic search of PubMed, Scopus, and Web of Science identified original studies employing MCLs for aortic simulation. Eligible studies were categorized into predefined themes: (I) (bio)mechanical aortic characterization, (II) hemodynamics, (III) device testing, (IV) diagnostics, and (V) training. Data on MCL configurations, aortic models, and study objectives were synthesized narratively. Results: Eighty-four studies met the inclusion criteria. Twenty-five investigated aortic biomechanics, 23 hemodynamics, 22 device or product testing, 13 validated diagnostic imaging techniques, and one training application. Models included porcine (n = 22), human cadaveric (n = 7), canine (n = 1), ovine (n = 1), bovine (n = 1), and 3D-printed or molded aortic phantoms (n = 55). MCLs were employed to study parameters such as aortic stiffness, flow dynamics, dissection propagation, endoleaks, imaging accuracy, and device performance. Conclusions: This review provides a comprehensive overview of MCL applications in aortic research. MCLs represent a versatile pre-clinical platform for studying aortic pathophysiology and testing endovascular therapies under controlled conditions. Standardized reporting frameworks are now required to improve reproducibility and accelerate translation to patient-specific planning. Full article

Parkinson’s disease (PD) is characterized by pathological changes in the substantia nigra, which in its early stages may manifest as structural and functional asymmetries between the two hemispheres. Microwave imaging has recently emerged as a promising non-invasive tool to detect subtle dielectric variations. In the context of Parkinson’s disease, such contrasts are expected to arise from the underlying physiological alterations in brain tissue, although their magnitude has not yet been fully characterized. In this work, we investigate the feasibility of differential microwave imaging, where detection is based on permittivity contrasts, through a controlled phantom study. A simple two-dimensional head phantom was constructed using a 3D-printed cylindrical container filled with water, incorporating a Teflon tube to represent the substantia nigra. The tube was filled with hot water, whose gradual cooling emulated small dielectric changes. Since the dielectric properties of water vary linearly with temperature over 0.5–3 GHz, we first validated this dependence through both numerical analysis and experimental measurements. Four antennas were then employed in a differential imaging configuration, with image reconstruction performed via the multi-frequency bi-focusing algorithm. The results show that the system can successfully detect a dielectric contrast corresponding to a temperature variation as small as 0.4 °C, equivalent to approximately 0.17% in relative permittivity. While the exact dielectric changes associated with PD remain to be determined, these results demonstrate that the proposed approach is sensitive to very small contrasts, supporting the potential of differential microwave imaging as a candidate tool for future investigations into Parkinson’s disease detection. Full article

Background: Photon-counting computed tomography (PCCT) represents a major technological advance in clinical CT imaging, offering superior spatial resolution, enhanced material discrimination, and potential radiation dose reduction compared to conventional energy-integrating detector systems. As the first clinically approved PCCT scanner becomes available, establishing a comprehensive characterization of its image quality is essential to understand its performance and clinical impact. Methods: Image quality was evaluated using a commercial quality assurance phantom with acquisition protocols typically used for three anatomical regions—head, abdomen/thorax, and inner ear—representing diverse clinical scenarios. Each region was scanned using both ultra-high-resolution (UHR, 120 × 0.2 mm slices) and conventional (144 × 0.4 mm slices) protocols. Conventional metrics, including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), slice thickness accuracy, and uniformity, were assessed following international standards. Task-based analysis was also performed through target transfer function (TTF), noise power spectrum (NPS), and detectability index (d′) to evaluate diagnostic relevance. Results: UHR protocols provided markedly improved spatial resolution, particularly in the inner ear imaging, as confirmed by TTF analysis, though with increased noise and reduced low-contrast detectability in certain conditions. CT numbers showed linear correspondence with known attenuation coefficients across all protocols. Conclusions: This study establishes a detailed technical characterization of the first clinical PCCT scanner, demonstrating significant improvements in terms of spatial resolution and accuracy of the quantitative image analysis, while highlighting the need for noise–contrast optimization in high-resolution imaging. Full article

Additive manufacturing (AM) has rapidly evolved due to its design flexibility, ability to enable personalized fabrication, and reduced material waste. In the medical field, fused filament fabrication (FFF) facilitates the production of individualized anatomical models for surgical preparation, education, medical imaging, and calibration. However, the lack of filaments with X-ray attenuation similar to that of biological hard tissues limits their use in radiological imaging. To address this limitation, a radiopaque filament was developed by incorporating gadolinium oxide (Gd₂O₃) into a biodegradable poly(lactic acid) (PLA) matrix at 1, 3, and 5 wt.%. Thermal and rheological properties were characterized using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), and melt flow index (MFI) analyses, revealing minor variations that did not affect printability under standard FFF conditions (200 °C nozzle, 60 °C build plate, 0.12 mm layer height). Microstructural analysis via field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), elemental mapping, and micro-computed tomography (micro-CT) confirmed homogeneous Gd₂O₃ dispersion without nozzle blockage. Radiopacity was evaluated using gyroid infill cubes, and increasing Gd₂O₃ content enhanced X-ray attenuation, with 3 wt.% Gd₂O₃ reaching Hounsfield Unit (HU) values comparable to cortical bone. Finally, the L1 vertebra phantom fabricated from the 3 wt.% Gd₂O₃ filament exhibited mean HU values of approximately +200 to +250 HU at 50% infill density (trabecular bone region) and around +1000 HU at 100% infill density (cortical bone region), demonstrating the filament’s potential for producing cost-effective, radiopaque, and biodegradable phantoms for computed tomography (CT) imaging. Full article

Breast tissue-mimicking phantoms are essential tools for validating microwave imaging systems designed for early breast cancer detection. In this work, we report the fabrication and comprehensive characterization of oil-in-gelatin phantoms emulating normal, benign, and malignant breast tissues. The phantoms were manufactured with controlled mixtures of kerosene, safflower oil, and gelatin, and their dielectric properties were experimentally evaluated using a free-space transmission method with a Vector Network Analyzer across the 100 MHz–10 GHz range. Results demonstrated significant contrast in permittivity and conductivity among the different tissue types, consistent with values reported in the literature. Long-term stability was confirmed for up to six months under controlled storage. Additional structural and thermal characterization was performed using Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA), providing insight into molecular composition and thermal response. The proposed method enables reproducible, low-cost, and stable phantom fabrication, offering reliable tissue models to support experimental validation and optimization of microwave-based breast cancer detection systems. Full article

Photon-counting computed tomography (PCCT) represents a major technological innovation compared to conventional CT, offering improved spatial resolution, reduced electronic noise, and intrinsic spectral capabilities. These advances open new perspectives for synergy with radiomics, a field that extracts quantitative features from medical images. The ability of PCCT to generate multiple types of datasets, including high-resolution conventional images, iodine maps, and virtual monoenergetic reconstructions, increases the richness of extractable features and potentially enhances radiomics performance. This narrative review investigates the current evidence on the interplay between PCCT and radiomics in cardiothoracic imaging. Phantom studies demonstrate reduced reproducibility between PCCT and conventional CT systems, while intra-scanner repeatability remains high. Nonetheless, PCCT introduces additional complexity, as reconstruction parameters and acquisition settings significantly may affect feature stability. In chest imaging, early studies suggest that PCCT-derived features may improve nodule characterization, but existing machine learning models, such as those applied to interstitial lung disease, may require recalibration to accommodate the new imaging paradigm. In cardiac imaging, PCCT has shown particular promise: radiomic features extracted from myocardial and epicardial tissues can provide additional diagnostic insights, while spectral reconstructions improve plaque characterization. Proof-of-concept studies already suggest that PCCT radiomics can capture myocardial aging patterns and discriminate high-risk coronary plaques. In conclusion, evidence supports a growing synergy between PCCT and radiomics, with applications already emerging in both lung and cardiac imaging. By enhancing the reproducibility and richness of quantitative features, PCCT may significantly broaden the clinical potential of radiomics in computed tomography. Full article

Experimental measurement of dose distributions is a pivotal step in the quality assurance of radiotherapy treatments, especially for those relying on high delivery accuracy such as hadron therapy. This study investigated the response of a polymer gel dosimeter to determine its suitability in performing geometric beam characterizations for hadron therapy under high-quenching conditions. Different extraction energies of proton and carbon ion beams were considered. Gel dose–response linearity and long-term stability were confirmed through optical measurements. Gel phantoms were irradiated with pencil beams and analyzed via magnetic resonance imaging. A multi-echo T₂-weighted sequence was used to reconstruct depth–dose profiles and transversal distributions acquired by the gels, which were benchmarked against reference data. As expected, a response-quenching effect in the Bragg peak region was noted. Nonetheless, the studied gel formulation proved reliable in acquiring the geometric characteristics of the beams, even without correcting for the quenching effect. Indeed, depth–dose distributions acquired by the gels showed an excellent agreement with measured particle range with respect to reference values, with mean discrepancies of 0.5 ± 0.2 mm. Single-spot transverse FWHM values at increasing depths also presented an average agreement within 1 mm with values determined with radiochromic films, thus supporting the excellent spatial resolving capabilities of the dosimetric gel. Full article