Search Results (1,901)

Objectives: This study investigates whether scan time in the high-resolution magnetic resonance imaging (MRI) of human embryos can be reduced without compromising spatial resolution by applying zero-shot self-supervised learning (ZS-SSL), a deep-learning-based reconstruction method. Methods: Simulations using a numerical phantom were conducted to evaluate spatial resolution across various acceleration factors (AF = 2, 4, 6, and 8) and signal-to-noise ratio (SNR) levels. Resolution was quantified using a blur-based estimation method based on the Sparrow criterion. ZS-SSL was compared to conventional compressed sensing (CS). Experimental imaging of a human embryo at Carnegie stage 21 was performed at a spatial resolution of (30 μm)³ using both retrospective and prospective undersampling at AF = 4 and 8. Results: ZS-SSL preserved spatial resolution more effectively than CS at low SNRs. At AF = 4, image quality was comparable to that of fully sampled data, while noticeable degradation occurred at AF = 8. Experimental validation confirmed these findings, with clear visualization of anatomical structures—such as the accessory nerve—at AF = 4; there was reduced structural clarity at AF = 8. Conclusions: ZS-SSL enables significant scan time reduction in high-resolution MRI of human embryos while maintaining spatial resolution at AF = 4, assuming an SNR above approximately 15. This trade-off between acceleration and image quality is particularly beneficial in studies with limited imaging time or specimen availability. The method facilitates the efficient acquisition of ultra-high-resolution data and supports future efforts to construct detailed developmental atlases. Full article

Timely and accurate monitoring of crop nitrogen (N) status is essential for precision agriculture. UAV-based hyperspectral remote sensing offers high-resolution data for estimating plant nitrogen concentration (PNC), but its cost and complexity limit large-scale application. This study compares the performance of UAV hyperspectral data (S185 sensor) with simulated multispectral data from DJI Phantom 4 Multispectral (P4M), PlanetScope (PS), and Sentinel-2A (S2) in estimating winter wheat PNC. Spectral data were collected across six growth stages over two seasons and resampled to match the spectral characteristics of the three multispectral sensors. Three variable selection strategies (one-dimensional (1D) spectral reflectance, optimized two-dimensional (2D), and three-dimensional (3D) spectral indices) were combined with Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), and Partial Least Squares Regression (PLSR) to build PNC prediction models. Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. Among models, SVM and RFR showed consistent effectiveness across strategies. These findings highlight the potential of low-cost multispectral platforms for practical crop N monitoring. Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms. Full article

Introduction: Although lipomas are common benign tumors found in adults, lipomas of the bladder are extremely rare. Bladder lipomas are infrequently reported in the urologic literature, with only 19 cases published worldwide. These can present as a mass on cystoscopy and cause irritative voiding symptoms, depending on their location. Upon transurethral resection, seeing fat can be concerning for a perforation, as lipoma can be mistaken for extravesical fat. Hence, familiarity with this rare entity is of paramount importance for urologists to prevent unnecessary investigations and interventions that are needed in case of a true bladder perforation. Case presentation: This study presents a case of bladder lipoma in a 73-year-old male with end-stage renal disease who presented for pretransplant urologic evaluation due to microscopic hematuria and irritative lower urinary tract symptoms (LUTS). During cystoscopy, a bladder mass was seen, and a transurethral resection of the bladder tumor (TURBT) revealed bright yellow adipose tissue immediately underneath the bladder mucosa. Concerns about perforation were obviated when seeing intact detrusor muscle underneath, visually confirming the integrity of the bladder wall. The resection was completed, and the CT scan was re-read with the radiologist, which confirmed the presence of a lipoma that was missed pre-operatively due to patient’s oliguria and collapsed bladder. No catheter drainage or cystogram was performed based on these findings. Outcome: The patient healed without any complications. Histopathology confirmed the diagnosis of a mature lipoma. The patient was cleared for transplant from a urologic standpoint and had a successful renal transplantation without delay. Discussion: This case documents the anomalous occurrence of a lipoma within the bladder and supports maintaining a broad differential, including liposarcoma, angiomyolipoma, and other non-malignant fatty tumors during the evaluation of a bladder mass. Full article

The red imported fire ant (RIFA; Solenopsis invicta) is an invasive species that severely threatens ecology, agriculture, and public health in Taiwan. In this study, the feasibility of applying multispectral imagery captured by unmanned aerial vehicles (UAVs) to detect red fire ant mounds was evaluated in Fenlin Township, Hualien, Taiwan. A DJI Phantom 4 multispectral drone collected reflectance in five bands (blue, green, red, red-edge, and near-infrared), derived indices (normalized difference vegetation index, NDVI, soil-adjusted vegetation index, SAVI, and photochemical pigment reflectance index, PPR), and textural features. According to analysis of variance F-scores and random forest recursive feature elimination, vegetation indices and spectral features (e.g., NDVI, NIR, SAVI, and PPR) were the most significant predictors of ecological characteristics such as vegetation density and soil visibility. Texture features exhibited moderate importance and the potential to capture intricate spatial patterns in nonlinear models. Despite limitations in the analytics, including trade-offs related to flight height and environmental variability, the study findings suggest that UAVs are an inexpensive, high-precision means of obtaining multispectral data for RIFA monitoring. These findings can be used to develop efficient mass-detection protocols for integrated pest control, with broader implications for invasive species monitoring. Full article

In this work, we provide a promising way to alleviate the Hubble tension within the framework of Myrzakulov $f(R,T)$ gravity. The latter incorporates both curvature and torsion under a non-special connection. We consider the $f(R,T)=R+\alpha R^2$ class, which leads to modified Friedmann equations and an effective dark energy sector. Within this class, we make specific connection choices in order to obtain a Hubble function that coincides with that of $\Lambda$CDM at early times while yielding higher $H_0$ values at late times. The reason behind this behavior is that the dark energy equation of state exhibits phantom behavior, which is known to be a sufficient mechanism for alleviating the $H_0$ tension. A full observational comparison with various datasets, including the Cosmic Microwave Background (CMB), is required to test the viability of this scenario. Strictly speaking, the present work does not provide a complete solution to the Hubble tension but rather proposes a promising way to alleviate it. Full article

Proton therapy has emerged as a highly precise and tissue-sparing radiotherapy technique, capitalizing on the unique energy deposition pattern of protons characterized by the Bragg peak. Ensuring treatment accuracy relies on calibration phantoms, often composed of tissue-equivalent polymeric materials. This study investigates the dosimetric behavior of four commonly used polymers—Parylene, Epoxy, Lexan, and Mylar—by analyzing their linear energy transfer (LET) values and Bragg curve characteristics across various proton energies. Experimental LET data were collected and used to train and evaluate the predictive power for Bragg peak of multiple artificial intelligence models, including kNN, SVR, MLP, RF, LWRF, XGBoost, 1D-CNN, LSTM, and BiLSTM. These algorithms were optimized using 10-fold cross-validation and assessed through statistical error and performance metrics including MAE, RAE, RMSE, RRSE, CC, and R². Results demonstrate that certain AI models, particularly RF and LWRF, accurately (in terms of all evaluation metrics) predict Bragg peaks in Epoxy polymers, reducing the reliance on costly and time-consuming simulations. In terms of CC and R² metrics, the LWRF model demonstrated superior performance, achieving scores of 0.9969 and 0.9938, respectively. However, when evaluated against MAE, RMSE, RAE, and RRSE metrics, the RF model emerged as the top performer, yielding values of 12.3161, 15.8223, 10.3536, and 11.4389, in the same order. Additionally, the SVR model achieved the highest number of statistically significant differences when compared pairwise with the other eight models, showing significance against six of them. The findings support the use of AI as a robust tool for designing reliable calibration phantoms and optimizing proton therapy planning. This integrative approach enhances the synergy between materials science, medical physics, and data-driven modeling in advanced radiotherapy systems. Full article

Three-dimensional imaging technologies are increasingly used in breast reconstructive and plastic surgery due to their potential for efficient and accurate preoperative assessment and planning. This study systematically evaluates the accuracy and consistency of six commercially available 3D scanning applications (apps)—Structure Sensor, 3D Scanner App, Heges, Polycam, SureScan, and Kiri—in reconstructing the female torso. To avoid variability introduced by human subjects, a silicone breast mannequin model was scanned, with fiducial markers placed at known anatomical landmarks. Manual distance measurements were obtained using calipers by two independent evaluators and compared to digital measurements extracted from 3D reconstructions in Blender software. Each scan was repeated six times per application to ensure reliability. SureScan demonstrated the lowest mean error (2.9 mm), followed by Structure Sensor (3.0 mm), Heges (3.6 mm), 3D Scanner App (4.4 mm), Kiri (5.0 mm), and Polycam (21.4 mm), which showed the highest error and variability. Even the app using an external depth sensor (Structure Sensor) showed no statistically significant accuracy advantage over those using only the iPad’s built-in camera (except for Polycam), underscoring that software is the primary driver of performance, not hardware (alone). This work provides practical insights for selecting mobile 3D scanning tools in clinical workflows and highlights key limitations, such as scaling errors and alignment artifacts. Future work should include patient-based validation and explore deep learning to enhance reconstruction quality. Ultimately, this study lays the foundation for more accessible and cost-effective 3D imaging in surgical practice, showing that smartphone-based tools can produce clinically useful scans. Full article

Measurable changes in electrophysiology have been documented in spaceflight, creating a pathway for disease genesis and progression in astronauts. These electrophysiology changes can be measured using potential difference (PD). A probe to measure PD was developed and is used clinically on Earth; this probe relies on fluid perfusion to establish an electrical connection to make PD measurements. The changes to fluid behavior in microgravity and partial gravity (including lunar and Martian gravity) drives the need to test this probe in a spaceflight environment. Here, we test the PD probe in a novel nasal cavity phantom in parabolic flight, simulating microgravity, lunar gravity, Martian gravity, and hypergravity conditions across 37 parabolas. The results are evaluated across gravity conditions using the Wilcoxon Rank Sum test. We record no statistically significant difference in probe PD measurements in 1 g, microgravity, lunar gravity, and hypergravity (approximately 1.8 g) conditions, reaching a NASA Technology Readiness Level 6. Martian gravity findings are inconclusive. Perfusion-based PD probes are therefore successfully demonstrated for use in spaceflight operation in microgravity, lunar gravity, and hypergravity environments; this establishes a foundation for moving towards the in-space testing of perfusion-based probes in astronauts. Full article

Conventional detectors based on ionization chambers, semiconductors, or thermoluminescent materials generally cannot be used to verify the in vivo dose delivered during brachytherapy treatments with γ-ray sources. However, certain adaptations and alternative methods, such as the use of miniaturized detectors or other specialized techniques, have been explored to address this limitation. One approach to solving this problem involves the use of dosimetric materials based on efficient scintillation crystals, which can be placed in the patient’s body using a long optical fiber inserted intra-cavernously, either in front of or next to the tumor. Scintillation crystals with a density close to that of tissue can be used in any location, including the respiratory tract, as they do not interfere with dose distribution. However, in many cases of radiation therapy, the detector may need to be positioned behind the target. In such cases, the use of heavy, high-density, and high-Z_eff scintillators is strongly preferred. The delivered radiation dose was registered using the radioluminescence response of the crystal scintillator and recorded with a compact luminescence spectrometer connected to the scintillator via a long optical fiber (so-called fiber-optic dosimeter). This proposed measurement method is completely non-invasive, safe, and can be performed in real time. To complete the abovementioned task, scintillation detectors based on YAG:Ce (ρ = 4.5 g/cm³; Z_eff = 35), LuAG:Ce (ρ = 6.75 g/cm³; Z_eff = 63), and GAGG:Ce (ρ = 6.63 g/cm³; Z_eff = 54.4) garnet crystals, with different densities ρ and effective atomic numbers Z_eff, were used in this work. The results obtained are very promising. We observed a strong linear correlation between the dose and the scintillation signal recorded by the detector system based on these garnet crystals. The measurements were performed on a specially prepared phantom in the brachytherapy treatment room at the Oncology Center in Bydgoszcz, where in situ measurements of the applied dose in the 0.5–8 Gy range were performed, generated by the ¹⁹²Ir (394 keV) γ-ray source from the standard Fexitron Elektra treatment system. Finally, we found that GAGG:Ce crystal detectors demonstrated the best figure-of-merit performance among all the garnet scintillators studied. Full article

This paper presents the PRONOBIS project, an ultrasound-only, robotically assisted, deep learning-based system for prostate scanning and biopsy treatment planning. The proposed system addresses the challenges of precise prostate segmentation, reconstruction and inter-operator variability by performing fully automated prostate scanning, real-time CNN-transformer-based image processing, 3D prostate reconstruction, and biopsy needle position planning. Fully automated prostate scanning is achieved by using a robotic arm equipped with an ultrasound system. Real-time ultrasound image processing utilizes state-of-the-art deep learning algorithms with intelligent post-processing techniques for precise prostate segmentation. To create a high-quality prostate segmentation dataset, this paper proposes a deep learning-based medical annotation platform, MedAP. For precise segmentation of the entire prostate sweep, DAF3D and MicroSegNet models are evaluated, and additional image post-processing methods are proposed. Three-dimensional visualization and prostate reconstruction are performed by utilizing the segmentation results and robotic positional data, enabling robust, user-friendly biopsy treatment planning. The real-time sweep scanning and segmentation operate at 30 Hz, which enable complete scan in 15 to 20 s, depending on the size of the prostate. The system is evaluated on prostate phantoms by reconstructing the sweep and by performing dimensional analysis, which indicates 92% and 98% volumetric accuracy on the tested phantoms. Three-dimansional prostate reconstruction takes approximately 3 s and enables fast and detailed insight for precise biopsy needle position planning. Full article

As yet, no study has investigated the use of a research magnetic resonance imaging (MRI) scanner to support undergraduate medical radiation science (MRS) students in developing their MRI knowledge and practical skills (competences). The purpose of this study was to test an innovative program for a total of 10 s- and third-year students of a MRS course to enhance their MRI competences. The study involved an experimental, two-week MRI learning program which focused on practical MRI scanning of phantoms and healthy volunteers. Pre- and post-program questionnaires and tests were used to evaluate the competence development of these participants as well as the program’s educational quality. Descriptive statistics, along with Wilcoxon signed-rank and paired t-tests, were used for statistical analysis. The program improved the participants’ self-perceived and actual MRI competences significantly (from an average of 2.80 to 3.20 out of 5.00, p = 0.046; and from an average of 34.87% to 62.72%, Cohen’s d effect size: 2.53, p < 0.001, respectively). Furthermore, they rated all aspects of the program’s educational quality highly (mean: 3.90–4.80 out of 5.00) and indicated that the program was extremely valuable, very effective, and practical. Nonetheless, further evaluation should be conducted in a broader setting with a larger sample size to validate the findings of this feasibility study, given the study’s small sample size and participant selection bias. Full article

Laser energy is widely used as a selective photothermal heating agent in cancer treatment, standing out for not relying on ionizing radiation. However, in vivo tests have highlighted the need to develop irradiation techniques that allow precise control over the illuminated area, adapting it to the tumor size to further minimize damage to surrounding healthy tissue. To address this challenge, a proof of concept based on a laser irradiation system has been designed, enabling control over energy, exposure time, and irradiated area, using galvanometric mirrors. The control software, implemented in Python, employs a set of cameras (visible and infrared) to detect and monitor real-time thermal distributions in the region of interest, transmitting this information to a microcontroller responsible for adjusting the laser power and controlling the scanning process. Image alignment procedures, tunning of the controller’s gain parameters and the impact of the different engineering parameters are illustrated on a dedicated setup. As proof of concept, this approach has demonstrated the ability to irradiate a phantom of black modeling clay within an area of up to 5 cm × 5 cm, from 15 cm away, as well as to monitor and regulate the temperature over time (5 min). Full article

This paper presents a dual-band antenna designed for integration into eyewear. The antenna is intended for a system supporting visually impaired individuals, where a wearable camera integrated into glasses transmits data to a remote receiver. To enhance system reliability within indoor environments, the proposed design supports both fifth-generation (5G) wireless communication and Wi-Fi networks. The compact antenna is specifically dimensioned for integration within eyeglass temples and operates in the 3.5 GHz and 5.8 GHz frequency bands. Prototype measurements, conducted using a human head phantom, validate the antenna’s performance. The results demonstrate good impedance matching across the desired frequency bands and a maximum gain of at least 4 dBi in both bands. Full article

As data exchange demands increase also in widespread wearable technologies, transitioning to higher bandwidths and mmWave frequencies (30–300 GHz) is essential. This shift raises concerns about RF exposure. At such high frequencies, the most crucial human tissue for RF power absorption is the skin, since EMF penetration is superficial. It becomes thus very important to assess how the model used to represent the skin in numerical dosimetry studies affects the estimated level of absorbed power. The present study, for the first time, assesses the absorbed power density (APD) using FDTD simulations on two realistic human models in which: (i) the skin has a two-layer structure made of the stratum corneum and the viable epidermis and dermis layers, and (ii) the skin is modelled as a homogeneous dermis stratum. These results were compared with ones using flat phantom models, with and without the stratified skin. The exposure assessment study was performed with two sources (a wearable patch antenna and a plane wave) tuned to 28 GHz. For the wearable antenna, the results evidence that the exposure levels obtained when using the homogeneous version of the models are always lower than the levels in the stratified skin version with percentage differences from 16% to 30%. This trend is more noticeable with the female model. In the case of plane wave exposure, these differences were less pronounced and lower than 11%. Full article

Background and Objectives: Dental adhesives augmented with magnetic nanoparticles (MNPs) have been proposed to prevent microleakages. MNPs dispersed in a dental adhesive reduce the thickness of the adhesive layer applied in a magnetic field and enhance the bond strength by favoring the penetration of the adhesive into dentinal tubules. However, the restoration’s color has been found to be affected by the MNPs. This study tests the hypothesis that MNP coating can alleviate the esthetic impact of magnetic dental adhesives. Materials and Methods: We synthesized Fe₃O₄ MNPs with silica coating (MNPs-SiO₂), calcium-based coating (MNPs-Ca), and no coating. Their morphology was studied using transmission electron microscopy (TEM) and scanning electron microscopy (SEM). Their chemical composition was assessed by energy-dispersive X-ray spectroscopy (EDX), and magnetic properties were measured using a vibrating sample magnetometer. FTIR spectroscopy was used to evaluate the polymerization of the MNP-laden adhesive. We prepared cavities in molar phantoms divided in four groups (n = 15 each) restored using the same adhesive with different MNP contents: Group 0 (G0)—no MNPs, G1—MNPs-SiO₂, G2—MNPs-Ca, and G3—uncoated MNPs. The restoration’s color was quantified in the CIELAB color space using a dental spectrophotometer. Results: MNPs-SiO₂ were globular, whereas MNPs-Ca had a cubic morphology. The SiO₂ layer was 73.1 nm ± 9.9 nm thick; the Ca(OH)₂ layer was 19.97 nm ± 2.27 nm thick. The saturation magnetization was 18.6 emu/g for MNPs-SiO₂, 1.0 emu/g for MNPs-Ca, and 65.7 emu/g for uncoated MNPs. MNPs had a marginal effect on the adhesive’s photopolymerization. The mean color difference between G0 and G2 was close to the 50:50% acceptability threshold, whereas the other groups were far apart from G0. The mean whiteness index of G2 did not differ significantly from that of G0; G1 deviated marginally from G0, whereas G3 differed significantly from G0. Conclusions: These results suggest that MNP coating can mitigate the influence of MNP-laden dental adhesives on the color of restorations. Full article