Signal-to-noise Research Articles

A hybrid steganography and watermark algorithm for copyright protection by using multiple embedding approaches

In this modern era, it has become much simpler to replicate, sell, and copy the copyright owners' works without their permission as a result of the expansion of digitalization, and it is difficult to identify such violations, posing a threat to the creators' and copyright owners' rights. For many years, the internet has been regarded as one of the most serious threats to copyright, and the content available has varying levels of copyright protection. On the internet, there are numerous copyrighted works, including e-books, movies, news, and so on. Therefore, by using watermarking and steganography techniques, these issues can be solved, which are based on the author's signature information or logo. This paper concluded that the techniques of discrete cosine transform (DCT), discrete wavelet transform (DWT), one-time pad (OTP), and playfair are highly effective when used together to watermark an image or embed a secret message, our lab results validate that our algorithm scheme is robust against several sets of attacks, where the algorithm was assessed by computation of many evaluation metrics such as mean square error (MSE), signal-to-noise ratio (SNR), and peak signal-to-noise ratio (PSNR).

Dose optimization in newborn abdominal radiography: Assessing the added value of additional filtration on radiation dose and image quality using an anthropomorphic phantom

BackgroundAbdominal radiographs remain useful in newborns. Given the high radiation sensitivity of this population, it is necessary to optimize acquisition techniques to minimize radiation exposure. ObjectiveEvaluate the effects of three additional filtrations on radiation dose and image quality in abdominal X-rays of newborns using an anthropomorphic phantom. Material and methodAbdominal radiographs of an anthropomorphic newborn phantom were performed using acquisition parameters ranging from 55 to 70 kV and from 0.4 to 2.5 mAs, without and with three different additional filtrations: 0.1 mm copper (Cu) + 1 mm aluminum (Al), 0.2 mm copper + 1 mm aluminum, and 2 mm aluminum. For each X-ray the dose area product (DAP) was measured, the signal-to-noise ratio (SNR) was calculated, and image quality (IQ) was evaluated by two blinded radiologists using the absolute visual grading analysis (VGA) method. ResultsAdding an additional filtration resulted in a significant reduction in DAP, with a decrease of 42% using 2 mm Al filtration, 65% with 0.1 mm Cu + 1 mm Al filtration, and 78% with 0.2 mm Cu + 1 mm Al filtration (p < 0.01). The addition of 2 mm aluminum filtration does not significantly decrease the SNR (p = 0.31), CNR (p = 0.52) or the IQ (p = 0.12 and 0.401 for reader 1 and 2, respectively). However, adding copper-containing filtration leads to a significant decrease in, SNR, CNR and IQ. ConclusionAdding a 2 mm Al additional filtration for abdominal radiographs in newborns can significantly reduce the radiation dose without causing a significant decrease in image quality.

A novel dynamic scale factor designed for recovering global TWS changes

For time-variable satellite gravity solutions of GRACE and GRACE-FO in terms of spherical harmonics coefficients, the Scale Factor (SF) is often used to recover the close to “true” signal of Terrestrial Water Storage (TWS) anomalies. However, the conventional SF method has some limitations that may hinder its effectiveness, including: (1) their dependency on input hydrological models that may lead to divergent estimations of SFs; (2) the arbitrary choice of filter strength, which may not be representative in different regions; (3) limited consideration of SF in the temporal dynamics (the conventional SF was fixed value) for monthly varied TWS. Here, we propose a new Dynamic SF method to overcome these limitations and increase accuracy of the restored global TWS changes. This method involves: (1) the Bayesian Three-Cornered Hat (BTCH) method is applied to merge three sets of hydrological products into an optimal hydrological dataset to be used for estimating a unique SF, (2) the anisotropic DDK3 filter (found to be numerically optimal) is applied to suppress the correlated noise, and (3) an iterative Kalman filter process is formulated and implemented to estimate monthly Dynamic SF corresponding to monthly global TWS fields. The Dynamic SF outperformed an ordinary SF method in terms of the Root Mean Squared Error (RMSE), the Mean Absolute Error (MAE), and the Signal to Noise Ratio (SNR), which were found to be improved by 30.8%, 32.2%, and 41.3%, respectively. Moreover, the recovered TWS using the Dynamic SF method showed a good agreement with the GRACE/GRACE-FO RL06 mascon solutions of the CSR and that of JPL regarding the long-term trend, seasonal, and interannual variations.

Investigation of agricultural waste and ZrB2 nanoparticles with reinforcement in aluminum alloy matrix

Agricultural waste has the potential to serve several purposes, such as reinforcement. In recent times, researchers have incorporated agricultural waste into various materials with the aim of enhancing their qualities. By acting as a kind of reinforcement, it has the potential to decrease the quantity of agricultural waste that needs further processing. This work enhances the area of advanced materials by examining the characteristics of Al 7175 alloy reinforced with zirconium diboride (ZrB2) nanoparticles and rice husk ash, which is a byproduct of agriculture. Understanding and improving the wear resistance of composites is crucial in several industrial applications. This study involves the incorporation of ZrB2 nanoparticles into the Al 7175 alloy at three distinct concentrations, with the addition of 2.5 % rice husk. This study examines the correlation between wear parameters and responses (Cf), including friction force (FF), wear rate (Sf), and friction coefficient. Sliding distance, load, composition, and speed are among the wear parameters. The aforementioned combinations result in a load of 25.2 N, a rotational speed of 400 rpm, a sliding distance of 71.2 m, and a composition of 5 %. Taguchi signal-to-noise ratio (SNR) analysis is used to identify optimal combinations for minimizing Cf, Sf, and FF. Confirmation tests are conducted in order to ensure that the results align with the expected optimal combinations. Data scientists may also use an Artificial Neural Network (ANN) model as a valuable tool. It utilizes input data to forecast replies. The ANN model demonstrates strong performance throughout testing, validation, and training, with an overall prediction rate of 87.873 %. The study's results indicate that reducing the load and speed, while increasing the concentration of ZrB2 nanoparticles, may effectively decrease the wear rate. In addition, the use of rice husk enhances the wear resistance of the base alloy by 28 %. The alloy Al 7175 may experience a reduction in wear rate and friction coefficients by the incorporation of 2.5 % rice husk and 5 % ZrB2 nanoparticles.

Experimental analysis for comparison of wireless transmission technologies: Wi-Fi, Bluetooth, ZigBee and LoRa for mobile multi-robot in hostile sites

This research paper conducts a thorough comparison of four prominent transmission technologies suitable for mobile robots operating in challenging environments. Emphasizing key factors such as signal strength, noise resistance, and data transfer efficiency, the study aims to identify the optimal communication solution in hostile conditions. The exploration delves into the intricacies of received signal strength indication (RSSI) and signal-to-noise ratio (SNR), revealing distinctive traits and trade-offs among the technologies. Navigating through the complexities of frequency bands, modulation types, and communication topologies, the paper examines the impact of obstacles, energy consumption dynamics, and potential real-world applications. Beyond contributing to the fields of robotics and communication, the study offers practical insights for stakeholders seeking resilient and efficient transmission methods for mobile robotic applications. Advocating for long range (LoRa) as the preferred transmission technology in hostile environments, the paper highlights its unmatched immunity to noise, stability, and minimal energy consumption. These findings provide valuable guidance for technology choices in collaborative mobile robot operations under challenging conditions. This research sets the stage for future developments in robotic communication, underscoring the crucial role of selecting the right transmission means for mission-critical applications in hostile environments.

Enhancing the accuracy of low-cost thermocouple devices through deep-wavelet neural network calibration

Data collection using thermocouple sensors in low-cost data acquisition is prone to noise interference, which could reduce the data quality. Noise sources such as cold junction compensators, electromagnetic interference, and Johnson noise can significantly affect the reliability and accuracy of conventional measurements. This study aims to improve the quality of thermocouple sensor readings on low-cost data acquisition using calibration method based on deep learning and the denoising process using a wavelet transform. This taken approach successfully increase the accuracy value of 97.67% with a mean absolute error (MAE) of 0.2. The precision also increases of 262.7% as indicated by the result of signal-to-noise ratio (SNR) with a value of 105.29 dB. Comparative analysis was carried out against National Instruments® device and it was found that deep-wavelet method had a lower and higher of MAE and SNRdB values of 16.67% and 0.8% respectively. This study shows that the denoising-calibration method with deep-wavelet can improve the accuracy and reliability of data from low-cost thermocouple devices.

Reliable Long-Term Serial Evaluation of Cochlear Function Using Pulsed Distortion-Product Otoacoustic Emissions: Analyzing Levels and Pressure Time Courses.

To date, there is no international standard on how to use distortion-product otoacoustic emissions (DPOAEs) in serial measurements to accurately detect changes in the function of the cochlear amplifier due, for example, to ototoxic therapies, occupational noise, or the development of regenerative therapies. The use of clinically established standard DPOAE protocols for serial monitoring programs appears to be hampered by multiple factors, including probe placement and calibration effects, signal-processing complexities associated with multiple sites of emission generation as well as suboptimal selection of stimulus parameters. Pulsed DPOAEs were measured seven times within 3 months for f2 = 1 to 14 kHz and L2 = 25 to 80 dB SPL in 20 ears of 10 healthy participants with normal hearing (mean age = 32.1 ± 9.7 years). L1 values were computed from individual optimal-path parameters derived from the corresponding individual DPOAE level map in the first test session. Three different DPOAE metrics for evaluating the functional state of the cochlear amplifier were investigated with respect to their test-retest reliability: (1) the interference-free, nonlinear-distortion component level (LOD), (2) the time course of the DPOAE-envelope levels, LDP(t), and (3) the squared, zero-lag correlation coefficient () between the time courses of the DPOAE-envelope pressures, pDP(t), measured in two sessions. The latter two metrics include the two main DPOAE components and their state of interference. Collated over all sessions and frequencies, the median absolute difference for LOD was 1.93 dB and for LDP(t) was 2.52 dB; the median of was 0.988. For the low (f2 = 1 to 3 kHz), mid (f2 = 4 to 9 kHz), and high (f2 = 10 to 14 kHz) frequency ranges, the test-retest reliability of LOD increased with increasing signal to noise ratio (SNR). On the basis of the knowledge gained from this study on the test-retest reliability of pulsed DPOAE signals and the current literature, we propose a DPOAE protocol for future serial monitoring applications that takes into account the following factors: (1) separation of DPOAE components, (2) use of individually optimal stimulus parameters, (3) SNR of at least 15 dB, (4) accurate pressure calibration, (5) consideration of frequency- and level-dependent test-retest reliabilities and corresponding reference ranges, and (6) stimulus levels L2 that are as low as possible with sufficient SNR to capture the nonlinear functional state of the cochlear amplifier operating at its highest gain.

Highly Sensitive Biomimetic Crack Pressure Sensor with Selective Frequency Response.

High-sensitivity sensors in practical applications face the issue of environmental noise interference, requiring additional noise reduction circuits or filtering algorithms to improve the signal-to-noise ratio (SNR). To address this issue, this study proposes a biomimetic crack pressure sensor with selective frequency response based on hydrogel dampers. The core of this research is to construct a biomimetic crack pressure sensor with selective frequency response using the high-pass filtering characteristics of gelatin-chitosan hydrogels. This design, inspired by the slit sensilla and stratum corneum structure of spider legs, delves into the material properties and principles of hydrogel dampers, exploring their application in biomimetic crack pressure sensors, including parameter selection, structural design, and performance optimization. By delving into the nuanced characteristics and working principles of hydrogel dampers, their integration in biomimetic crack pressure sensors is examined, focusing on aspects like parameter selection, structural engineering, and performance enhancement to selectively sieve out low-frequency noise and transmit target vibrational signals. Experimental results demonstrate that this innovative sensor, while suppressing low-frequency vibration signals, can selectively detect high-frequency signals with high sensitivity. At different vibration frequencies, the relative change in resistance exceeds 200%, and the sensor sensitivity is 7 × 104 kPa-1. Furthermore, this sensor was applied to human voice detection, and the corresponding results verified its frequency-selective performance evidently. This study not only proposes a new design for pressure sensors but also offers fresh insights into the application of biomimetic crack pressure sensors in intricate environments.

Investigation of triaxial cables and microdetectors in small field dosimetry

Background. Small field dosimetry presents unique challenges with source occlusion, lateral charged particle equilibrium and detector size. As detector volume decreases, signal strength declines while noise increases, deteriorating the signal-to-noise ratio (SNR). This issue may be compounded by triaxial cables connecting detectors to electrometers. However, effects of cables, critical for precision dosimetry, are often overlooked. There is a need to evaluate triaxial cable and detector impacts on SNR in small fields. The purpose of this study is to evaluate the influence of triaxial cables and microdetectors on signal-to-noise ratios in small-field dosimetry. This study also aims to establish the importance of cable quality assurance for measurement accuracy. Methods. Six 9.1 m length triaxial cables from different manufacturers were tested with six microdetectors (microDiamond, PinPoint, EDGE, Plastic scintillator, microSilicon, SRS-Diode). A 6 MV photon beam (TrueBeam) was used, with a water phantom at 5 cm depth with 0.5 × 0.5 cm2 to 10 × 10 cm2 fields at 600 MU min−1. Readings were acquired using cable-detector permutations with a dedicated electrometer (except the scintillator which has its own). Cables had differing connector types, conductor materials, insulation, and diameters. Detectors had various sensitive volumes, materials, typical signals, and bias voltages. Results. Normalized field output correction factors (FOFs) relative differences of 13.4% and 4.6% between the highest and lowest values across triaxial cables for 0.5 × 0.5 cm2 and 1 × 1 cm2 fields, respectively. The maximum difference in FOF between any cable-detector combinations was 0.2% for the smallest field size. No consistent FOF trend was observed across all detectors when increasing cable diameter. Additionally, the non-normalized FOF differences of 0.9% and 0.3% were observed between cables for 0.5 × 0.5 cm2 and 1 × 1 cm2 fields, respectively. Conclusions. Regular triaxial cable quality assurance is critical for precision small field dosimetry. A national protocol is needed to standardize cable evaluations/calibrations, particularly for small signals (<pC) from modern detectors. This could enhance measurement accuracy and treatment delivery with advanced small-field radiotherapy techniques that promise improved patient outcomes. Further studies should expand detector and cable models tested across institutions to establish robust quality control guidelines.

Enhancing diagnostic performance and image quality in coronary CT angiography: Impact of SnapShot Freeze 2 algorithm across varied heart rates in stent patients.

To investigate the enhancement of image quality achieved through the utilization of SnapShot Freeze 2 (SSF2), a comparison was made against the results obtained from the original SnapShot Freeze algorithm (SSF) and standard motion correction (STND) in stent patients undergoing coronary CT angiography (CCTA) across the entire range of heart rates. A total of 118 patients who underwent CCTA, were retrospectively included in this study. Images of these patients were reconstructed using three different algorithms: SSF2, SSF, and STND. Objective assessments include signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), diameters of stents and artifact index (AI). The image quality was subjectively evaluated by two readers. Compared with SSF and STND, SSF2 had similar or even higher quality in the parameters (AI, SNR, CNR, inner diameters) of coronary artery, stent, myocardium, MV (mitral valve), TV (tricuspid valve), AV (aorta valve), and PV (pulmonary valve), and aortic root (AO). Besides the above structures, SSF2 also demonstrated comparable or even higher subjective scores in atrial septum (AS), ventricular septum (VS), and pulmonary artery root (PA). Furthermore, the enhancement in image quality with SSF2 was significantly greater in the high heart rate group compared to the low heart rate group. Moreover, the improvement in both high and low heart rate groups was better in the SSF2 group compared to the SSF and STND group. Besides, when using the three algorithms, an effect of heart rate variability on stent image quality was not detected. Compared to SSF and STND, SSF2 can enhance the image quality of whole-heart structures and mitigate artifacts of coronary stents. Furthermore, SSF2 has demonstrated a significant improvement in the image quality for patients with a heart rate equal to or higher than 85bpm.

Signal-to-Noise Ratio in Estimating and Testing the Mediation Effect: Structural Equation Modeling versus Path Analysis with Weighted Composites.

Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models are determined by the subjectively assigned scales of the latent variables. Thus, conclusions in existing studies comparing structural equation modeling (SEM) and path analysis with weighted composites (PAWC) on the accuracy and precision of the estimates of the indirect effect in mediation analysis have little validity. Instead of comparing the size on estimates of the indirect effect between SEM and PAWC, this article compares parameter estimates by signal-to-noise ratio (SNR), which does not depend on the metrics of the latent variables once the anchors of the latent variables are determined. Results show that PAWC yields greater SNR than SEM in estimating and testing the indirect effect even when measurement errors exist. In particular, path analysis via factor scores almost always yields greater SNRs than SEM. Mediation analysis with equally weighted composites (EWCs) also more likely yields greater SNRs than SEM. Consequently, PAWC is statistically more efficient and more powerful than SEM in conducting mediation analysis in empirical research. The article also further studies conditions that cause SEM to have smaller SNRs, and results indicate that the advantage of PAWC becomes more obvious when there is a strong relationship between the predictor and the mediator, whereas the size of the prediction error in the mediator adversely affects the performance of the PAWC methodology. Results of a real-data example also support the conclusions.

Improved Denoising of Cryo-Electron Microscopy Micrographs with Simulation-Aware Pretraining.

Cryo-electron microscopy (cryo-EM) has emerged as a potent technique for determining the structure and functionality of biological macromolecules. However, limited by the physical imaging conditions, such as low electron beam dose, micrographs in cryo-EM typically contend with an extremely low signal-to-noise ratio (SNR), impeding the efficiency and efficacy of subsequent analyses. Therefore, there is a growing demand for an efficient denoising algorithm designed for cryo-EM micrographs, aiming to enhance the quality of macromolecular analysis. However, owing to the absence of a comprehensive and well-defined dataset with ground truth images, supervised image denoising methods exhibit limited generalization when applied to experimental micrographs. To tackle this challenge, we introduce a simulation-aware image denoising (SaID) pretrained model designed to enhance the SNR of cryo-EM micrographs where the training is solely based on an accurately simulated dataset. First, we propose a parameter calibration algorithm for simulated dataset generation, aiming to align simulation parameters with those of experimental micrographs. Second, leveraging the accurately simulated dataset, we propose to train a deep general denoising model that can well generalize to real experimental cryo-EM micrographs. Comprehensive experimental results demonstrate that our pretrained denoising model achieves excellent denoising performance on experimental cryo-EM micrographs, significantly streamlining downstream analysis.

Enhancement of single-lead dry-electrode ECG through wavelet denoising

Neonatal electrocardiogram (ECG) monitoring is an important diagnostic tool for identifying cardiac issues in infants at birth. Long-term remote neonatal dry-electrode ECG monitoring solutions can be an additional step for preventive healthcare measures. In these solutions, power and computationally efficient embedded signal processing techniques for denoising newborn ECGs can assist in increasing neonatal medical wearable time. Wavelet denoising is an appropriate denoising mechanism with low computational complexity that can be implemented on embedded microcontrollers for long-term remote ECG monitoring. Discrete wavelet transform (DWT) denoising for neonatal dry-electrode ECG using different wavelet families is investigated. The wavelet families and mother wavelets used include Daubechies (db1, db2, db3, db4, and db6), symlets (sym5), and coiflets (coif5). Different levels of added white Gaussian noise (AWGN) were added to 19 newborn ECG signals, and denoising was performed to select the appropriate wavelets for neonatal dry-electrode ECG. The selected wavelets then undergo real noise additions of baseline wander and electrode motion to determine their robustness and accuracy. Signal-to-noise ratio (SNR), mean squared error (MSE), and power spectral density (PSD) are used to examine denoising performance. db1, db2, and db3 wavelets are eliminated from analysis where the 30 dB AWGN led to negative SNR improvement for at least one newborn ECG, removing important ECG information. db4 and sym5 are eliminated from selection due to their different waveform morphology compared to the dry-electrode newborn ECG’s QRS complex. db6 and coif5 are selected due to their highest SNR improvement and lowest MSE of 6.26 × 10−6 and 1.65 × 10−7 compared to other wavelets, respectively. Their wavelet shapes are more like a newborn ECG’s QRS morphology, validating their selection. db6 and coif5 showed similar denoising performance, decreasing electrode motion and baseline wander noisy ECG signals by 10 dB and 14 dB, respectively. Further denoising of inherent dry-electrode noise is observed. DWT with coif5 or db6 wavelets is appropriate for denoising newborn dry-electrode ECGs for long-term neonatal dry-electrode ECG monitoring solutions under different noise types. Their similarity to newborn dry-electrode ECGs yields accurate and robust reconstructed denoised newborn dry-electrode ECG signals.

A Side Lobe Level Reduction Method Using Simulated Annealing Algorithm in a Uniform Arc Array

In general, the amplitude-weighting method for an acoustic transducer array is widely used to improve the array directivity and reject disturbances. This paper presents a method to effectively reduce the side lobe level while minimizing the main lobe width increase. This is done using the simulated annealing algorithm (SAA) for a uniformly spaced arc array of omnidirectional underwater acoustic transducers, even at low signal-to-noise ratio (SNR). We propose a new cost function for the SAA and obtain the weighting coefficients for all array elements using the SAA, and next compare them with various amplitude weighting methods. Through simulation and comparison, it is verified that the proposed method is effective in beamforming of the uniform arc array of underwater acoustic transducers.

Regional evaluation of global geopotential models and three types of digital elevation models with ground-based gravity and GNSS/levelling data using several techniques over Sudan

Abstract To evaluate the performance of the global geopotential models (GGMs) in a more unbiased way, ground-based gravity and GNSS/levelling datasets are highly required. In this study, the eight latest releases of the satellite-only and combined GGMs are evaluated on the regional scale using the available terrestrial gravity and GNSS/Levelling data over Sudan, considering the spectral consistency issue by applying the spectral enhancement method (SEM). The evaluation process consists of three stages: firstly, the eight GGMs are evaluated globally with each other by using different degree variances in terms of geoid heights, gravity anomalies, and signal-to-noise ratio (SNR); secondly, the GGMs are compared against the Earth Gravitational Model 2008 (EGM2008) on a regional scale over Sudan; thirdly, apply the SEM strategy by incorporating high (SEM_WITHOUT_RTM technique) and very-high (SEM technique) frequencies of the gravity field spectrum from the EGM2008 and high-resolution residual terrain model (RTM), respectively. For reliable robustness of the latter evaluation process, three different DEMs are used, namely, SRTM30, ASTER30, and GTOPO30. Our findings on the evaluation process using SEM_WITHOUT_RTM technique show improved gravity anomalies solutions regarding differences of standard deviations (STD) from 19–20.7 mGal to about 14 mGal. When applying the SEM technique, more improvements are achieved, providing STD differences in gravity anomalies and geoid heights of about 12 mGal and 45 cm, respectively. Among the three applied DEMs, it has been found that despite the slight refinements, the ASTER30 and GTOPO30 models show better performance than the SRTM30 model.

Performance Analysis of BER and SNR Performance in High-QAM Modulations Using Advancements in MIMO Systems

Wireless communications is one of the most active areas of technology development of our time. This development is being driven primarily by the transformation of what has been largely a medium for supporting voice telephony into a medium for supporting other services, such as the transmission of video, images, text, and data. Today, the widely deployed network type is based on a centralized approach that requires a network point of access, commonly called the Access Point (AP), to serves as a gateway between the mobile device and the Internet. The obtained results demonstrate that spatial diversity along with the power of STBC significantly improves the error performance in frequency selective wireless fading channels. The BER level is depend on the modulation type, SNR value and channel behavior. Modulation schemes that we have used in this paper are 4-QAM, 8-QAM, 16-QAM and 64-QAM which further improved using forward error correction codes (FEC). A comparison is made between the diversity gains of MIMO systems in terms of BER for high QAM modulation scheme. This work presents, a simulation toll MATLAB R2023a used for model implemented using Nakagami channel to study the performance analysis of Bit Error rate (BER) V/S Signal to Noise ratio (SNR). Keywords: AWGN, BER, Fading Channel, MIMO System, Nakagami, OFDM, QAM Modulation, SNR, STBC etc.

A birdcage transmit, 24-channel conformal receive array coil for sensitive 31P magnetic resonance spectroscopic imaging of the human brain at 7 T.

Phosphorus (31P) magnetic resonance spectroscopic imaging (MRSI) can serve as a critical tool for more direct quantification of brain energy metabolism, tissue pH, and cell membrane turnover. However, the low concentration of 31P metabolites in biological tissue may result in low signal-to-noise ratio (SNR) in 31P MRS images. In this work, we present an innovative design and construction of a 31P radiofrequency coil for whole-brain MRSI at 7 T. Our coil builds on current literature in ultra-high field 31P coil design and offers complete coverage of the brain, including the cerebellum and brainstem. The coil consists of an actively detunable volume transmit (Tx) resonator and a custom 24-channel receive (Rx) array. The volume Tx resonator is a 16-rung high-pass birdcage coil. The Rx coil consists of a 24-element phased array composed of catered loop shapes and sizes built onto a custom, close-fitting, head-shaped housing. The Rx array was designed to provide complete coverage of the head, while minimizing mutual coupling. The Rx configuration had a mean reflection coefficient better than -20 decibels (dB) when the coil was loaded with a human head. The mean mutual coupling ( ) among Rx elements, when loaded with a human head, was -16 dB. In phantom imaging, the phased array produced a central SNR that was 4.4-fold higher than the corresponding central SNR when operating the 31P birdcage as a transceiver. The peripheral SNR was 12-fold higher when applying the optimized phased array. In vivo 3D 31P MRSI experiments produced high-quality spectra in the cerebrum gray and white matter, as well as in the cerebellum. Characteristic phosphorus metabolites related to adenosine triphosphate metabolism and cell membrane turnover were distinguishable across all brain regions. In summary, our results demonstrate the potential of our novel coil for accurate, whole-brain 31P metabolite quantification.

Computed chest radiography for total body irradiation: image quality and clinical feasibility.

In myeloablative total body irradiation (TBI), lung shielding&#xD;blocks are used to reduce the dose to the lungs and hence decrease the risk of radiation&#xD;pneumonitis. Some centers are still using mega-Volt (MV) imaging with dedicated&#xD;silver halide-based films during simulation and treatment for lung delineation and&#xD;position verification. However, the availability of these films has recently become&#xD;an issue. This study examines the clinical performance of a computed radiography&#xD;(CR) solution in comparison to radiographic films and potential improvement of image&#xD;quality by filtering and post-processing. We compared BaFBrI-based CR&#xD;plates to radiographic films. First, images of an aluminum block were analyzed to&#xD;assess filter impact on scatter reduction. Secondly, a dedicated image quality phantom&#xD;was used to assess signal linearity, signal-to-noise ratio (SNR), contrast and spatial&#xD;resolution. Ultimately, a clinical performance study involving two impartial observers&#xD;was conducted on an anthropomorphic chest phantom, employing visual grading&#xD;analysis (VGA). Various filter materials and positions as well as post-processing were&#xD;examined, and the workflow between CR and film was compared. CR&#xD;images exhibited high SNR and linearity but demonstrated lower spatial and contrast&#xD;resolution when compared to film. However, filtering improved contrast resolution&#xD;and SNR, while positioning filters inside the cassette additionally enhanced sharpness.&#xD;Image processing improved VGA scores, while additional filtering also resulted in&#xD;higher spine visibility scores. CR shortened TBI simulation by over 10 minutes for&#xD;one patient, alongside a dose reduction by order of 0.1 Gy. This study&#xD;highlights potential advantages of shifting from conventional radiographic film to CR&#xD;for TBI. Overall, CR with the incorporation of processing and filtering proves to&#xD;be suitable for TBI chest imaging. When compared to radiographic film, CR offers&#xD;advantages such as reduced simulation time and dose delivery, re-usability of image&#xD;plates and digital workflow integration.

Choosing a camera and optimizing system parameters for speckle contrast optical spectroscopy

Speckle contrast optical spectroscopy (SCOS) is an emerging camera-based technique that can measure human cerebral blood flow (CBF) with high signal-to-noise ratio (SNR). At low photon flux levels typically encountered in human CBF measurements, camera noise and nonidealities could significantly impact SCOS measurement SNR and accuracy. Thus, a guide for characterizing, selecting, and optimizing a camera for SCOS measurements is crucial for the development of next-generation optical devices for monitoring human CBF and brain function. Here, we provide such a guide and illustrate it by evaluating three commercially available complementary metal–oxide–semiconductor cameras, considering a variety of factors including linearity, read noise, and quantization distortion. We show that some cameras that are well-suited for general intensity imaging could be challenged in accurately quantifying spatial contrast for SCOS. We then determine the optimal operating parameters for the preferred camera among the three and demonstrate measurement of human CBF with this selected low-cost camera. This work establishes a guideline for characterizing and selecting cameras as well as for determining optimal parameters for SCOS systems.

An Optical Detection Model for Stratospheric Airships

This study proposes a numerical model to simulate the thermal characteristics of stratospheric airships (SA). This model introduces a simple yet accurate method for the selection of the optical bands for target detection based on multispectral features. The key to this model is the selection of the spectral bands in which a significant radiation difference exists between the target and its surrounding background. Using the signal-to-noise ratio (SNR), detection probability, and false alarm rate as model evaluation metrics, and based on the analysis of the radiation differences between the target and atmospheric background, it is found that there are two narrow bands possible for SA detection: one with a central wavelength of 8.83 µm and a bandwidth of 0.35 µm and the other with a central wavelength of 11.51 µm and a bandwidth of 0.34 µm. Further numerical simulations and theoretical analyses under varying space environments demonstrate that considerable detection potential can be achieved; thus, the presented optical detection model is useful for the night detection of SA targets.