Discrete interferences optimum beamformer in correlated signal and interfering noise

This paper introduces a significant special situation where the noise is a collection of D-plane interference signals and the correlated noise of D+1 is less than the number of array components. An optimal beamforming processor based on the minimum variance distortionless response (MVDR) generates and combines appropriate statistics for the D+1 model. Instead of the original space of the N-dimensional problem, the interference signal subspace is reduced to D+1. Typical antenna arrays in many modern communication networks absorb waves generated from multiple point sources. An analytical formula was derived to improve the signal to interference and noise ratio (SINR) obtained from the steering errors of the two beamformers. The proposed MVDR processor-based beamforming does not enforce general constraints. Therefore, it can also be used in systems where the steering vector is compromised by gain. Simulation results show that the output of the proposed beamformer based on the MVDR processor is usually close to the ideal state within a wide range of signal-to-noise ratio and signal-to-interference ratio. The MVDR processor-based beamformer has been experimentally evaluated. The proposed processor-based MVDR system significantly improves performance for large interference white noise ratio (INR) in the sidelobe region and provide an appropriate beam pattern.

Strategies for the Efficient Estimation of Soil Moisture through Spectroscopy: Sensitive Wavelength Algorithm, Spectral Resampling and Signal-to-Noise Ratio Selection

It is found that the remote sensing parameters such as spectral range, spectral resolution and signal-to-noise ratio directly affect the estimation accuracy of soil moisture content. However, the lack of research on the relationship between the parameters and estimation accuracy restricts the prolongation of application. Therefore, this study took the demand for this application as the foothold for developing spectrometry. Firstly, a method based on sensitivity analysis of soil radiative transfer model-successive projection algorithm (SA-SPA) was proposed to select sensitive wavelengths. Then, the spectral resampling method was used to select the best spectral resolution in the corresponding sensitive wavelengths. Finally, the noise-free spectral data simulated by the soil radiative transfer model was added with Gaussian random noise to change the signal-to-noise ratio, so as to explore the influence of signal-to-noise ratio on the estimation accuracy. The research results show that the estimation accuracy obtained through the SA-SPA (RMSEP < 12.1 g kg−1) is generally superior to that from full-spectrum data (RMSEP < 14 g kg−1). At selected sensitive wavelengths, the best spectral resolution is 34 nm, and the applicable signal-to-noise ratio ranges from 150 to 350. This study provides technical support for the efficient estimation of soil moisture content and the development of spectrometry, which comprehensively considers the common influence of spectral range, spectral resolution and signal-to-noise ratio on the estimation accuracy of soil moisture content.

Fiducial visibility on planar images during motion-synchronized tomotherapy treatments

Objective: Synchrony® is a motion management system on the Radixact® that uses planar kV radiographs to locate the target during treatment. The purpose of this work is to quantify the visibility of fiducials on these radiographs. Approach: A custom acrylic slab was machined to hold 8 gold fiducials of various lengths, diameters, and orientations with respect to imaging axis. The slab was placed on the couch at the imaging isocenter and planar radiographs were acquired perpendicular to the custom slab with varying thicknesses of acrylic on each side. Fiducial signal to noise ratio (SNR) and detected fiducial position error in millimeters were quantified. Main Results: The minimum output protocol (100 kVp, 0.8 mAs) was sufficient to detect all fiducials on both Radixact configurations when the thickness of the phantom was 20 cm. However, no fiducials for any protocol were detected when the phantom was 50 cm thick. The algorithm accurately detected fiducials on the image when the SNR was larger than 4. The MV beam was observed to cause RFI artifacts on the kV images and to decrease SNR by an average of 10%. Significance: This work provides the first data on fiducial visibility on kV radiographs from Radixact Synchrony treatments. The Synchrony fiducial detection algorithm was determined to be very accurate when sufficient SNR is achieved. However, a higher output protocol may need to be added for use with larger patients. This work provided groundwork for investigating visibility of fiducial-free solid targets in future studies and provided a direct comparison of fiducial visibility on the two Radixact configurations, which will allow for intercomparison of results between configurations.

Optimization of Spatial Resolution and Image Reconstruction Parameters for the Small-Animal MetisTM PET/CT System

The aim of this study was to investigate the optimization of spatial resolution and image reconstruction parameters related to image quality in an iterative reconstruction algorithm for the small-animal MetisTM PET/CT system. We used a homemade Derenzo phantom to evaluate the image quality by visual assessment, signal-to-noise ratio, contrast, coefficient of variation, and contrast-to-noise ratio of the 0.8 mm hot rods of 8 slices in the centre of the phantom PET images. A healthy mouse study was performed to analyze the influence of optimal reconstruction parameters and Gaussian post-filter FWHM. In the phantom study, the best image quality was obtained by placing the phantom at one end, keeping the central axis parallel to X-axis of the system, selecting iterations between 30 and 40, with a reconstruction voxel of 0.314 mm and a Gaussian post-filter FWHM of 1.57 mm. The optimization of spatial resolution can reach 0.6-mm. In the animal study, it was suitable to choose a voxel size of 0.472-mm, iterations between 30 and 40, and 2.36-mm Gaussian post-filter FWHM. Our results indicate that optimal imaging conditions and reconstruction parameters are necessary to obtain high-resolution images and quantitative accuracy, especially for the high-precision identification of tiny lesions.

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

Audio steganography is implemented based on three main features: capacity, robustness, and imperceptibility, but simultaneously implementing them is still a challenge. Embedding data at the Least Significant Bit (LSB) of the audio sample is one of the most implemented audio steganography methods because the method will give high capacity and imperceptibility. However, LSB has the lowest robustness among all common methods in audio steganography. To cater to this problem, researchers increased the depth of the embedding level from fourth to sixth and eighth LSB level to improve its robustness feature. However, consequently, the imperceptibility feature, which is commonly measured by Peak Signal to Noise Ratio (PSNR), is reduced due to the trade-off between imperceptibility and robustness. Currently, the lack of study on the estimation of the PSNR for audio steganography has caused the early assessment of the imperceptibility-robustness trade-off difficult. Therefore, a method to estimate PSNR, known as PSNR Estimator (PE), is introduced to enable early evaluation of imperceptibility feature for each stego-file produced by the audio steganography, which is important for the utilisation of embedding. The proposed PE estimates the PSNR based on the pattern collected from the embedment at different levels. From the evaluation, the proposed method has 99.9% of accuracy in estimating PSNR values at different levels. In comparison with the Mazdak Method, the proposed method performs better in all situations. In conclusion, the proposed PE can be used as a reference for embedding and further reducing the calculation complexity in finding the feasible value to minimise the trade-off between robustness and imperceptibility.

Performance of PROPELLER FSE T2WI in Reducing Metal Artifacts for Patients with Various Material Porcelain Fused To Metal Crown: A Preliminary Study

This study aimed to compare MRI quality between common fast spin echo T2 weighted imaging (FSE T2WI) with periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) FSE T2WI for patients with various porcelain fused to metal (PFM) crown and analyze the value of PROPELLER technique in reducing metal artifacts. Common FSE T2WI and PROPELLER FSE T2WI sequences for axial imaging of head were applied in participants with different PFM crowns: cobalt-chromium (Co-Cr) alloy, pure titanium (Ti), gold-palladium (Au-Pd) alloy. Two radiologists evaluated overall image quality of section in PFM using a 5-point scale qualitatively and measured the maximum artifact area and artifact signal-to-noise ratio (SNR) quantitatively. The metal crown with the least artifacts and the optimum image quality shown in common FSE T2WI and PROPELLER FSE T2WI were in Au–Pd alloy, Ti, and Co–Cr alloy order. PROPELLER FSE T2WI was superior to common FSE T2WI in improving image quality and reducing artifact area for Co-Cr alloy (17.0±0.2% smaller artifact area, p＜0.001) and Ti (11.6± 0.7 % smaller artifact area, p=0.005), but had similar performance compared to FSE T2WI for Au-Pd alloy. For all PFMs, PROPELLER FSE T2WI significantly reduced the signal-to-noise ratio (SNR) of artifact (393.57±89.75 VS. 214.05±70.45, p < 0.001) when compared to common FSE T2WI.Therefore, the different PFM crown generate varying degrees of metal artifacts in MRI, and the PROPELLER can effectively reduce metal artifacts especially in the PFM crown of Co-Cr alloy.

Application of Highly Flexible Adaptive Image Receive Coil for Lung MR Imaging Using Zero TE Sequence: Comparison with Conventional Anterior Array Coil

(1) Background: Highly flexible adaptive image receive (AIR) coil has become available for clinical use. The present study aimed to evaluate the performance of AIR anterior array coil in lung MR imaging using a zero echo time (ZTE) sequence compared with conventional anterior array (CAA) coil. (2) Methods: Sixty-six patients who underwent lung MR imaging using both AIR coil (ZTE-AIR) and CAA coil (ZTE-CAA) were enrolled. Image quality of ZTE-AIR and ZTE-CAA was quantified by calculating blur metric value, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of lung parenchyma. Image quality was qualitatively assessed by two independent radiologists. Lesion detection capabilities for lung nodules and emphysema and/or lung cysts were evaluated. Patients’ comfort levels during examinations were assessed. (3) Results: SNR and CNR of lung parenchyma were higher (both p < 0.001) in ZTE-AIR than in ZTE-CAA. Image sharpness was superior in ZTE-AIR (p < 0.001). Subjective image quality assessed by two independent readers was superior (all p < 0.05) in ZTE-AIR. AIR coil was preferred by 64 of 66 patients. ZTE-AIR showed higher (all p < 0.05) sensitivity for sub-centimeter nodules than ZTE-CAA by both readers. ZTE-AIR showed higher (all p < 0.05) sensitivity and accuracy for detecting emphysema and/or cysts than ZTE-CAA by both readers. (4) Conclusions: The use of highly flexible AIR coil in ZTE lung MR imaging can improve image quality and patient comfort. Application of AIR coil in parenchymal imaging has potential for improving delineation of low-density parenchymal lesions and tiny nodules.

Antigenic properties of the SARS-CoV-2 nucleoprotein are altered by the RNA admixture

Determining the presence of antibodies to the SARS-CoV-2 antigens is the best way to identify infected people, regardless of the development of symptoms of COVID-19. The nucleoprotein (NP) of the SARS-CoV-2 is an immunodominant antigen of the virus; anti-NP antibodies are detected in persons previously infected with the virus with the highest titers. Many test systems for detecting antibodies to SARS-CoV-2 contain NP or its fragments as antigen. The sensitivity and specificity of such test systems differ significantly, which can be explained by variations in the antigenic properties of NP caused by differences in the methods of its cultivation, isolation and purification. We investigated this effect for the Escherichia coli-derived SARS-CoV-2 NP, obtained from the cytoplasm in the soluble form. We hypothesized that co-purified nucleic acids that form a strong complex with NP might negatively affect NP’s antigenic properties. Therefore, we have established the NP purification method, which completely eliminates the RNA in the NP preparation. Two stages of RNA removal were used: treatment of the crude lysate of E. coli with RNase A and subsequent selective RNA elution with 2 M NaCl solution. The resulting NP without RNA has a significantly better signal-to-noise ratio when used as an ELISA antigen and tested with a control panel of serum samples with antibodies to SARS-CoV-2; therefore, it is preferable for in vitro diagnostic use. The same increase of the signal-to-noise ratio was detected for the free N-terminal domain of the NP. Complete removal of RNA complexed with NP during purification will significantly improve its antigenic properties, and the absence of RNA in NP preparations should be controlled during the production of this antigen.

Raman Signal Denoising Using Fully Convolutional Encoder Decoder Network

Raman spectroscopy is a vibrational method that gives molecular information rapidly and non-invasively. Despite its advantages, the weak intensity of Raman spectroscopy leads to low-quality signals, particularly with tissue samples. The requirement of high exposure times makes Raman a time-consuming process and diminishes its non-invasive property while studying living tissues. Novel denoising techniques using convolutional neural networks (CNN) have achieved remarkable results in image processing. Here, we propose a similar approach for noise reduction for the Raman spectra acquired with 10x lower exposure times. In this work, we developed fully convolutional encoder-decoder architecture (FCED) and trained them with noisy Raman signals. The results demonstrate that our model is superior (p-value <0.0001) to the conventional denoising techniques such as the Savitzky-Golay filter and wavelet denoising. Improvement in the signal-to-noise ratio values ranges from 20% to 80%, depending on the initial signal-to-noise ratio. Thus, we proved that tissue analysis could be done in a shorter time without any need for instrumental enhancement.

Research on Fast Compensation Algorithm for Interframe Motion of Multimedia Video Based on Manhattan Distance

To improve the video quality, aiming at the problems of low peak signal-to-noise ratio, poor visual effect, and low bit rate of traditional methods, this paper proposes a fast compensation algorithm for the interframe motion of multimedia video based on Manhattan distance. The absolute median difference based on wavelet transform is used to estimate the multimedia video noise. According to the Gaussian noise variance estimation result, the active noise mixing forensics algorithm is used to preprocess the original video for noise mixing, and the fuzzy C-means clustering method is used to smoothly process the noisy multimedia video and obtain significant information from the multimedia video. The block-based motion idea is to divide each frame of the video sequence into nonoverlapping macroblocks, find the best position of the block corresponding to the current frame in the reference frame according to the specific search range and specific rules, and obtain the relative Manhattan distance between the current frame and the background of multimedia video using the Manhattan distance calculation formula. Then, the motion between the multimedia video frames is compensated. The experimental results show that the algorithm in this paper has a high peak signal-to-noise ratio and a high bit rate, which effectively improves the visual effect of the video.