SNR Enhancement Research Articles

Radiation dose reduction and image quality in pediatric paranasal sinus CT: with automatic tube current modulation and iterative reconstruction technique.

Our objective is to evaluate radiation dose and image quality in pediatric paranasal sinus computed tomography (CT) with automatic tube current modulation (ATCM) and sinogram-affirmed iterative reconstruction algorithm (SAFIRE). CT scans from 80 patients were divided into two groups: Group A [80 kVp, pitch 1.5, 40 mAs, the filtered back projection (FBP) algorithm] and Group B (70 kVp, pitch 3, ATCM with reference at 40 mAs, SAFIRE strengths 1-5). We have evaluated image quality and radiation dose. Group B demonstrated significantly lower volume computed tomography dose index, dose-length product, and effective dose than Group A (0.13±0.03 vs. 1.57±0.01mGy, 2.27±0.82 vs. 19.88±2.01mGy·cm, and 0.0081±0.0017 vs. 0.079±0.013mSv, respectively; P<.001). Increasing SAFIRE strengths correlated with noise reduction and SNR enhancement. Group B's noise and SNRsoft at SAFIRE strength 5 were comparable with Group A. Images reconstructed with SAFIRE strength 5 in Group B exhibit comparable image quality with FBP in Group A.

Improvement of MRS at ultra-high field using a wireless RF array.

We aim to assess a straightforward technique to enhance spectral quality in the brain, particularly in the cerebellum, during 7 T MRI scans. This is achieved through a wireless RF array insert designed to mitigate signal dropouts caused by the limited transmit field efficiency in the inferior part of the brain. We recently developed a wireless RF array to improve MRI and 1H-MRS at 7 T by augmenting signal via inductive coupling between the wireless RF array and the MRI coil. In vivo experiments on a Siemens 7 T whole-body human scanner with a Nova 1Tx/32Rx head coil quantified the impact of the dorsal cervical array in improving signal in the posterior fossa, including the cerebellum, where the transmit efficiency of the coil is inherently low. The 1H-MRS experimental protocol consisted of paired acquisition of data sets, both with and without the RF array, using the semi-LASER and SASSI sequences. The overall results indicate that the localized 1H-MRS is improved significantly in the presence of the array. Comparison of in vivo 1H-MRS plots in the presence versus absence of the array demonstrated an average SNR enhancement of a factor of 2.2. LCModel analysis reported reduced Cramér-Rao lower bounds, indicating more confident fits. This wireless RF array can significantly increase detection sensitivity. It may reduce the RF transmission power and data acquisition time for 1H-MRS and MRI applications, specifically at 7 T, where 1H-MRS requires a high-power RF pulse. The array could provide a cost-effective and efficient solution to improve detection sensitivity for human 1H-MRS and MRI in the regions with lower transmit efficiency.

Detection of Large Dynamic Range Acoustic Signal Using OPD-Based Fiber-Optic Interferometric Demodulation With SNR Enhancement

Detection of Large Dynamic Range Acoustic Signal Using OPD-Based Fiber-Optic Interferometric Demodulation With SNR Enhancement

A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST).

To develop a SNR enhancement method for chemical exchange saturation transfer (CEST) imaging using a denoising convolutional autoencoder (DCAE), and compare its performance with state-of-the-art denoising methods. The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of 1D convolutions, nonlinearity applications and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in-vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric. In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirms the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared to other methods. While no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings. The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared to other methods.

A new SNR enhancement method in MFL detection for microcracks on rough surface based on the ferromagnetic lift-off layer

ABSTRACT In conventional magnetic flux leakage (MFL) detection research, the surface of the workpiece is usually assumed to be smooth. However, the actual roughness will have an impact on the detection. To solve the problem of crack detection on rough surfaces, a method using ferromagnetic lift-off media instead of air lift-off was proposed. Firstly, the smooth surface and the rough surface model were established, and the difference of the leakage magnetic field signal was compared through the simulations. Secondly, the air lift-off media was replaced with ferromagnetic lift-off media, and the enhancement effect of the ferromagnetic lift-off media on the SNR(signal-to-noise ratio,SNR) of the magnetic flux leakage signal of microcrack was analyzed. Then, by changing the ferromagnetic media layer thickness and permeability, the improvement of the these parameters on SNR of the magnetic leakage signal of microcracks was analyzed. Finally, it was verified by experiments that the method can improve SNR of magnetic flux leakage signal of microcrack on the rough workpiece surface to a certain extent. The SNR enhancement method provides a certain application reference for the practice of magnetic flux leakage detection of rough surface workpieces.

Efficient signal-to-noise ratio enhancement model for severely contaminated distributed acoustic sensing seismic data based on heterogeneous knowledge distillation

Distributed acoustic sensing (DAS) is an emerging seismic acquisition technique with great practical potential. However, various types of noise seriously corrupt DAS signals, making it difficult to recover signals, particularly in low signal-to-noise ratio (S/N) regions. Existing deep-learning methods address this challenge by augmenting data sets or strengthening the complex architecture, which can cause overdenoising and a computational power burden. Hence, the heterogeneous knowledge distillation (HKD) method is developed to more efficiently address the signal reconstruction under low S/N. HKD uses ResNet 20 as the teacher and student (T-S) model. It uses residual learning and skip connections to facilitate feature representation at deeper levels. The main contribution is the training of the T-S framework with different noise levels. The teacher model that is trained using slightly noisy data serves as a powerful feature extractor to capture more accurate signal features because high-quality data are easy to recover. By minimizing the difference between the outputs of T-S models, the student model that is trained using severely noisy data can distill the absent signal features from the teacher to improve its own signal recovery, which enables heterogeneous feature distillation. Furthermore, simultaneous positive and negative learning (P&amp;NL) is developed to extract more useful features from the teacher, enabling the T-S framework to learn from the predicted signal and noise during training. Consequently, a new loss function that combines student denoising loss and HKD loss weighted by P&amp;NL is developed to alleviate signal leakage. The experimental results demonstrate that the HKD achieves distinct and consistent signal recovery without increasing computational costs.

Simulation-Based Enhancement of SNR in Drone Communication through Uniform Linear Array Configurations

Simulation-Based Enhancement of SNR in Drone Communication through Uniform Linear Array Configurations

SNR Enhancement for BOTDA by DnCNN and Pulse Coding

SNR Enhancement for BOTDA by DnCNN and Pulse Coding

Remote photoplethysmography-based human vital sign prediction using cyclical algorithm.

This article aims to predict vital signs like heart rate (HR), respiration rate, and arterial oxygen saturation using ambient light video, eliminating chronic distortions through improved frame quality with BER estimation. The study employs the cascade residual CNN-FPNR technique for preprocessing and SNR enhancement using energy variance maximization. The image cascade network (ICNet) facilitates segmentation, achieving strong segmentation in low-light ambient videos. Remote photoplethysmography (iPPG) enables noncontact vital sign monitoring, predicting HR and respiratory rate (RR). An innovative noninvasive temperature and cyclical algorithm, incorporating principal component analysis and fast Fourier transform, evaluate patient HR and RR. To address challenges related to involuntary movements, a dynamic time-warping-based optimization method is used for precise region selection. The study introduces an intensity variance-based threshold analysis for arterial oxygen saturation level determination. Ultimately, the support vector machine (SVM) classification technique evaluates the ground truth, showcasing the system's promising potential for remote and accurate vital sign assessment.

31‐2: An Asynchronous Single‐Ended Touch Sensing Method for Y‐OCTA Using Adaptive TX Duty Control method

In this paper, it is introduced a new touch sensing method for the flexible OLED (Y‐OCTA) eliminating the chronic constraints on selecting touch sensing frequencies. In the prior art, the touch sensing frequencies have been limited to the display scan frequency(H‐sync) or its harmonics to avoid the interference effects between Touch and Display operations, which results in some weaknesses in external noise immunity for the Touch sensor. This paper proposes a method to overcome the constraints such that any sensing frequencies would be available, while preserving Display Noise immunity for Touch IC and display flicker‐free for Display as well. As a result, the proposed IC showed SNR enhancement of 17 dB without display flicker in the asynchronous sensing mode for the worst test image patterns having the strongest Display Noise. The proposed IC was fabricated on a 90‐nm CMOS process and its silicon area is 21.2mm 2.

Quartz tuning fork-based high sensitive photodetector by co-coupling photoelectric and the thermoelastic effect of perovskite.

This paper reports a new strategy for enhancing the photoresponse of a quartz tuning fork (QTF). A deposited light absorbing layer on the surface of QTF could improve the performance only to a certain extent. Herein, a novel strategy is proposed to construct a Schottky junction on the QTF. The Schottky junction presented here consists of a silver-perovskite, which has extremely high light absorption coefficient and dramatically high power conversion efficiency. The co-coupling of the perovskite's photoelectric effect and its related QTF thermoelastic effect leads to a dramatic improvement in the radiation detection performance. Experimental results indicate that the CH3NH3PbI3-QTF obtains two orders of magnitude enhancement in sensitivity and SNR, and the 1σ detection limit was calculated to be 1.9 µW. It was the first time that the QTF resonance detection and perovskite Schottky junction was combined for optical detection. The presented design could be used in photoacoustic spectroscopy and thermoelastic spectroscopy for trace gas sensing.

SNR enhancement of magnetic fields measurement with the diamond NV center using a compound filter system

SNR enhancement of magnetic fields measurement with the diamond NV center using a compound filter system

Fast numerical propagation in high-NA imaging using the resampling angular spectrum method.

Numerical propagation calculation is a fundamental research topic in optical engineering. The standard angular spectrum method (ASM) is accurate but time- and memory-consuming, especially for high-NA systems. In this work, we propose a fast and simple numerical propagation method, the resampling ASM (RS-ASM). Numerical propagation can be accelerated by combining a resampling technique with interpolation methods in the angular spectrum domain of a constrained object at the focal plane. RS-ASM has three main advantages: simple implementation, faster calculation than the standard ASM, and SNR enhancement. Here we validate RS-ASM using theory, simulation and experiment. Using the "bilinear" ASM with a proper resampling factor can result in a speed-up factor of up to 20x (for a transformation from the angular spectrum to the E field) and 4x (for a transformation from E field to the angular spectrum), together with a SNR improvement of approximately 2x. For an application example of Gerchberg-Saxton phase reconstruction, the "bilinear" RS-ASM can converge 2.6x faster than the standard ASM.

Retinalike Foveated Imaging through an Opaque Scattering Medium

Imaging through an opaque scattering medium, such as biological tissue, is of broad interest for many applications from physics to life sciences. Measuring the transmission matrix (TM) of the scattering medium is a versatile tool for this purpose. Previously, researchers are used to improving the image resolution by measuring a gigantic TM with a long sampling time. However, the low resolution and low SNR of the reconstructed images are still two obstacles to the adoption of such a technique. The foveal centralis of the human eye produces sharper vision than that from the retina's peripheral region. Inspired by this feature, we report the implementation of foveated scattering imaging with a multiresolution TM whose space-variant resolution feature can be flexibly adjusted. The enhancement of linear resolution and SNR of the foveated scattering imaging system by factors of 4 and 8.3, respectively, is demonstrated experimentally. Our bioinspired imaging method heuristically introduces foveal vision into scattering imaging, and thus paves the way for both high resolution and high SNR imaging through scattering medium concurrently monitoring the entire field of view.

SNR Enhancement for Multi-TE MRSI Using Joint Low-Dimensional Model and Spatial Constraints.

We present a novel method to enhance the SNR for multi-TE MR spectroscopic imaging (MRSI) data by integrating learned nonlinear low-dimensional model and spatial constraints. A deep complex convolutional autoencoder (DCCAE) was developed to learn a nonlinear low-dimensional representation of the high-dimensional multi-TE 1H spectroscopy signals. The learned model significantly reduces the data dimension thus serving as an effective constraint for noise reduction. A reconstruction formulation was proposed to integrate the spatiospectral encoding model, the learned model, and a spatial constraint for an SNR-enhancing reconstruction from multi-TE data. The proposed method has been evaluated using both numerical simulations and in vivo brain MRSI experiments. The superior denoising performance of the proposed over alternative methods was demonstrated, both qualitatively and quantitatively. In vivo multi-TE data was used to assess the improved metabolite quantification reproducibility and accuracy achieved by the proposed method. We expect the proposed SNR-enhancing reconstruction to enable faster and/or higher-resolution multi-TE 1H-MRSI of the brain, potentially useful for various clinical applications.

Analysis of Stray Light and Enhancement of SNR in DMD-Based Spectrometers.

Due to advantages such as the high efficiency of light utilization, small volume, and vibration resistance, digital micro-mirror device (DMD)-based spectrometers are widely used in ocean investigations, mountain surveys, and other field science research. In order to eliminate the stray light caused by DMDs, the stray light in DMD-based spectrometers was first measured and analyzed. Then, the stray light was classified into wavelength-related components and wavelength-unrelated components. Moreover, the noise caused by the stray light was analyzed from the perspective of encoding equation, and the de-noising decoding equation was deduced. The results showed that the accuracy range of absorbance was enhanced from [0, 1.9] to [0, 3.1] in single-stripe mode and the accuracy range of absorbance was enhanced from [0, 3.8] to [0, 6.3] in Hadamard transform (HT) multiple-stripe mode. A conclusion can be drawn that the de-noising strategy is feasible and effective for enhancing the SNR in DMD-based spectrometers.

Improving local SNR of a single-channel 54.6 mT MRI system using additional LC-resonator

Very-low field magnetic resonance imaging (VLF-MRI, B0 < 0.1T) has an essential application in medical imaging diagnosis because of its light weight and low cost. For single-channel RF coil VLF-MRI system, a planar spiral LC-resonator placed on the surface of samples was designed to improve the local SNR. First, an equivalent circuit model was established to evaluate the boosting effects on radiofrequency (RF) magnetic field and SNR. Second, the relationship between the resonant capacitance and the transmission coefficient was deduced according to the circuit model, and the appropriate resonant capacitance was obtained. Then, the influence of the diameter and the number of turns of the LC-resonator on the SNR is considered, and the structure of the LC-resonator was optimized to maximize the SNR. Finally, a phantom MRI experiment was carried out with our home-built 54.6 mT MRI system to compare the SNR of the experiment with the calculation, the SNR enhancement trend of the two was consistent. Additional experiments were conducted using orange and chicken leg to demonstrate the SNR enhancement abilities of the LC-resonator. The enhancement of SNR reached up to 1.8-fold and 2.2-fold depending on the distance between the sample and LC-resonator. For comparison, we conducted imaging experiments on surface receiving coil with the same parameters, and the results show that the SNR of the LC resonator is comparable to that of the surface coil. The reported LC-resonator provide a low-cost local enhancement method for VLF-MRI.

Simultaneous enhancement of fluorescence intensity, thermometric sensitivity and SNR of upconversion thermometers via optical field localization

The proposed 2D photonic crystal (PC)/Au/UCNPs upconverted platform can simultaneously enhance the detected signal intensity, SNR and thermometric sensitivity by creating extra amplified interfacial thermal fields around the UCNPs.

Phase Correction Based Snr Enhancement for Distributed Acoustic Sensing with Strong Environmental Background Interference

Phase Correction Based Snr Enhancement for Distributed Acoustic Sensing with Strong Environmental Background Interference

Heralded single-pixel imaging with high loss-resistance and noise-robustness

Imaging with non-classically correlated photon-pairs takes advantages over classical limits in terms of sensitivity and a signal-to-noise ratio. However, it is still a challenge to achieve a strong resilience to background noise and losses for practical applications. In this work, we present heralded single-pixel imaging that is remarkably robust against bright background noise and severe signal losses. Using a strong temporal correlation between a photon-pair and joint measurement-based imaging method, we achieve the suppression of noise up to 1000 times larger than the signal and also demonstrate the correlation-induced SNR enhancement factor of over 200 against 70 times larger noise and a 90% signal loss compared to non-time-gated classical imaging. Our work enables correlated imaging with a highly scalable photon capacity.