Signal-to-noise Research Articles

Mitigation of DMM-induced stripe patterns in synchrotron X-ray radiography through dynamic tilting.

In synchrotron X-ray radiography, achieving high image resolution and an optimal signal-to-noise ratio (SNR) is crucial for the subsequent accurate image analysis. Traditional methods often struggle to balance these two parameters, especially in situ applications where rapid data acquisition is essential to capture specific dynamic processes. For quantitative image data analysis, using monochromatic X-rays is essential. A double multilayer monochromator (DMM) is successfully used for this aim at the BAMline, BESSY II (Helmholtz Zentrum Berlin, Germany). However, such DMMs are prone to producing an unstable horizontal stripe pattern. Such an unstable pattern renders proper signal normalization difficult and thereby causes a reduction of the SNR. We introduce a novel approach to enhance SNR while preserving resolution: dynamic tilting of the DMM. By adjusting the orientation of the DMM during the acquisition of radiographic projections, we optimize the X-ray imaging quality, thereby enhancing the SNR. The corresponding shift of the projection during this movement is corrected in post-processing. The latter correction allows a good resolution to be preserved. This dynamic tilting technique enables the homogenization of the beam profile and thereby effectively reduces noise while maintaining high resolution. We demonstrate that data captured using this proposed technique can be seamlessly integrated into the existing radiographic data workflow, as it does not need hardware modifications to classical X-ray imaging beamline setups. This facilitates further image analysis and processing using established methods.

Design of calibration-free RF pulses for T -weighted single-slab 3D turbo-spin-echo sequences at 7T utilizing parallel transmission.

T -weighted turbo-spin-echo (TSE) sequences are a fundamental technique in brain imaging but suffer from field inhomogeneities at ultra-high fields. Several methods have been proposed to mitigate the problem, but were limited so far to nonselective three-dimensional (3D) measurements, making short acquisitions difficult to achieve when targeting very high resolution images, or needed additional calibration procedures, thus complicating their application. Slab-selective excitation pulses were designed for flexible placement utilizing the concept of k -spokes. Phase-coherent refocusing universal pulses were subsequently optimized with the Gradient Ascent Pulse Engineering algorithm and tested in vivo for improved signal homogeneity. Implemented within a 3D variable flip angle TSE sequence, these pulses led to a signal-to-noise ratio (SNR) improvement ranging from 10%to 30% compared to a two-dimensional (2D) T2w TSE sequence employing -shimmed pulses. field inhomogeneities could be mitigated and artifacts from deviations reduced. The concept of universal pulses was successfully applied. We present a pulse design method which provides a set of calibration-free universal pulses (UPs) for slab-selective excitation and phase-coherent refocusing in slab-selective TSE sequences.

Improving MR axon radius estimation in human white matter using spiral acquisition and field monitoring.

To compare MR axon radius estimation in human white matter using a multiband spiral sequence combined with field monitoring to the current state-of-the-art echo-planar imaging (EPI)-based approach. A custom multiband spiral sequence was used for diffusion-weighted imaging at ultra-high -values. Field monitoring and higher order image reconstruction were employed to greatly reduce artifacts in spiral images. Diffusion weighting parameters were chosen to match a state-of-the art EPI-based axon radius mapping protocol. The spiral approach was compared to the EPI approach by comparing the image signal-to-noise ratio (SNR) and performing a test-retest study to assess the respective variability and repeatability of axon radius mapping. Effective axon radius estimates were compared over white matter voxels and along the left corticospinal tract. Increased SNR and reduced artifacts in spiral images led to reduced variability in resulting axon radius maps, especially in low-SNR regions. Test-retest variability was reduced by a factor of approximately 1.5 using the spiral approach. Reduced repeatability due to significant bias was found for some subjects in both spiral and EPI approaches, and attributed to scanner instability, pointing to a previously unknown limitation of the state-of-the-art approach. Combining spiral readouts with field monitoring improved mapping of the effective axon radius compared to the conventional EPI approach.

Adaptive tunicate swarm optimization with partial transmit sequence for phase optimization in MIMO-OFDM

<span>Multiple-input multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) are widely utilized in wireless systems and maximum data rate communications. The MIMO-OFDM technology increases the efficiency of spectrum utilization. The peak-to-average-power ratio (PAPR) minimization in MIMO-OFDM is a complex task in wireless communications systems. In this research, an adaptive tunicate swarm optimization with partial transmit sequence (ATSO-PTS) algorithm is proposed for a reduction of PAPR in MIMO-OFDM. The nonsquare-matrix-based differential space time coding (N-DSTC) scheme is used for the encoding and decoding process of MIMO-OFDM. The N-DSTC encoding and decoding are linear error-correcting codes that are utilized for message transmission over noisy channels. The pre-specified quadrate phase shift keying (QPSK) symbol is deployed for the modulation and demodulation scheme. On the receiver side, the serial to parallel (S/P) conversion, and fast Fourier transform (FFT) are accomplished, alongside the received data bits being demodulated to obtain the output bits. The proposed ATSO-PTS method achieves better results according to performance metrices PAPR, bit error rate (BER) and signal-to-noise-ratio (SNR), with values of about 2.9, 0.01 and 0.025, respectively. This ensures superior results when compared to the existing methods of twin symbol hybrid optimization applied to partial transmit sequence (TSHO-PTS), selective level mapping and PTS (SLM-PTS), and particle swarm and grey wolf (PS-GW) with PTS, respectively.</span>

Combined Effect of Noise Reduction, FBS-Based Spectral Splitting, and Dynamic Range Compression of Speech Signal on Source Localization in Binaural Hearing Aids

Localizing sound sources in three spatial dimensions (azimuth, elevation, and distance) is critical for human hearing comfort. It relies on two binaural cues: interaural time difference (ITD) and interaural level difference (ILD). Cochlear or auditory nerve injury can result in sensorineural hearing loss (SNHL). Hearing aids enable people with sensorineural hearing loss to converse more effectively and hear better. However, there is an apprehension that the binaural hearing aids may degrade the localization cues, thus affecting the source localization. In response to this concern, the current study investigates how the binaural hearing aid algorithm affects source localization by adopting a cascaded structure of noise reduction technique (wiener filter) followed by filter bank summation (FBS) based spectral splitting and dynamic range compression for binaural dichotic presentation. Listening tests for seven different azimuth angles (-90⁰, -60⁰, -30⁰, 0⁰, 30⁰, 60⁰, and - 90⁰) were conducted on six listeners with normal hearing under different signal-to-noise ratio (SNR) conditions as well as on six subjects with mild bilateral sensorineural hearing impairment. Test stimuli included background glass-breaking sound and broadband noise for participants with normal hearing. In an experiment with hearing-impaired subjects, the glass-breaking sound served as one of the test stimuli. The result showed that these binaural hearing aid algorithms had no adverse effects on localization ability.

Image quality of the non-contrast BOOST cardiac magnetic resonance sequence to visualize the pulmonary veins in patients with atrial fibrillation

Abstract Background In patients with atrial fibrillation (AF), imaging examinations have an important role in planning ablation by imaging the pulmonary veins (PV). The PV anatomy is conventionally assessed before ablation using computer tomography (CT) or 3 dimensional (3D) contrast-enhanced cardiac magnetic resonance (CMR) imaging. The new 3-dimensional, free-breathing BOOST (Bright-blood and black-blOOd phase SensiTive inversion recovery) cardiac magnetic resonance (CMR) sequence is suitable for imaging the left atrium without the addition of contrast agent. Purpose The aim of our study was to investigate the BOOST sequence for the imaging of PVs, and the effect of heart rate and rhythm on image quality. Methods Forty-seven patients underwent and BOOST CMR before ablation, 25 of them had also left atrial CT angiography (CTA). The BOOST sequence was performed using T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) techniques. The image quality was analyzed using a subjective Likert scale and quantitatively by determining the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Heart rate and rhythm were assessed by 12-lead ECG. Results MTC-BOOST images were suitable for PVs analysis in all cases, whereas the assessment of PVs on T2prep-BOOST images was inadequate in the majority of cases due to artifacts. CTA showed the same PV anatomy as assessed with BOOST CMR. Based on the operating electrophysiologists’ subjective opinion, the quality of the CTA scans was better compared with BOOST sequence. Still, they found the CMR images appropriate for procedural planning in 43 out of 47 cases (91%). SNR and CNR values of the MTC-BOOST bright-blood images were higher if patients had sinus rhythm. We found a significant or nearly significant negative correlation between heart rate and the SNR and CNR values of MTC-BOOST bright-blood images. Conclusions MTC-BOOST images are suitable for visualisation of PVs, producing diagnostic image quality in 100% of cases. In the majority of cases, MTC-BOOST images were appropriate for procedural planning before ablation. Image quality is affected by the patients' heart rate and frequency. Figure 1: MTC BOOST bright blood image of the left atrium and the right pulmonary veins (arrows)

New scheme of cooperative compressed spectrum sensing

Abstract This study addresses key challenges in sparse signal recovery and compressed spectrum sensing (CSS), focusing on low signal-to-noise ratios (SNR), and the computational complexity of cooperative systems. Motivated by the need for faster and more accurate recovery techniques, we first investigate and generalize the Reduced-Set Matching Pursuit (RMP) algorithm, which overcomes the speed and accuracy limitations of conventional greedy algorithms. Secondly, we propose a novel spatial averaging technique that enhances detection performance by exploiting data from multiple users to counteract low SNR. Lastly, we integrate cooperation into CSS, further improving the detection capabilities during the recovery process. Compared to existing techniques like Joint Sparse Recovery (JSR) and CoSaMP, which face computational and accuracy constraints in real-time applications, the RMP algorithm, combined with the Virtual method (data transformation) and AND fusion rule, delivers superior performance than JSR methods. Moreover, spatial averaging significantly increases the probability of cooperative detection Q d , with SNR increasing linearly by a factor of L − 1 per channel. The results are validated through the implementation of SDR. These findings demonstrate the potential of RMP and cooperation to overcome current limitations in CSS, advancing the state-of-the-art in spectrum sensing for collaborative networks.

Improving Accuracy and Reproducibility of Cartilage T2 Mapping in the OAI Dataset Through Extended Phase Graph Modeling.

The Osteoarthritis Initiative (OAI) collected extensive imaging data, including Multi-Echo Spin-Echo (MESE) sequences for measuring knee cartilage T2 relaxation times. Mono-exponential models are used in the OAI for T2 fitting, which neglects stimulated echoes and B1 inhomogeneities. Extended Phase Graph (EPG) modeling addresses these limitations but has not been applied to the OAI dataset. To assess how different fitting methods, including EPG-based and exponential-based approaches, affect the accuracy and reproducibility of cartilage T2 in the OAI dataset. Retrospective. From OAI dataset, 50 subjects, stratified by osteoarthritis (OA) severity using Kellgren-Lawrence grades (KLG), and 50 subjects without OA diagnosis during OAI duration were selected (each group: 25 females, mean ages ~61 years). 3-T, two-dimensional (2D) MESE sequence. Femoral and tibial cartilages were segmented from DESS images, subdivided into seven sub-regions, and co-registered to MESE. T2 maps were obtained using three EPG-based methods (nonlinear least squares, dictionary matching, and deep learning) and three mono-exponential approaches (linear least squares, nonlinear least squares, and noise-corrected exponential). Average T2 values within sub-regions were obtained. Pair-wise agreement among fitting methods was evaluated using the stratified subjects, while reproducibility using healthy subjects. Each method's T2 accuracy and repeatability varying signal-to-noise ratio (SNR) were assessed with simulations. Bland-Altman analysis, Lin's concordance coefficient, and coefficient of variation assessed agreement, repeatability, and reproducibility. Statistical significance was set at P-value <0.05. EPG-based methods demonstrated superior T2 accuracy (mean absolute error below 0.5 msec at SNR > 100) compared to mono-exponential methods (error > 7 msec). EPG-based approaches had better reproducibility, with limits of agreement 1.5-5 msec narrower than exponential-based methods. T2 values from EPG methods were systematically 10-17 msec lower than those from mono-exponential fitting. EPG modeling improved agreement and reproducibility of cartilage T2 mapping in subjects from the OAI dataset. 3 TECHNICAL EFFICACY: Stage 1.

Assessing myocardial tissue in the acute setting with Photon-Counting CT (PCCT) in comparison with Cardiac Magnetic Resonance (CMR)

Abstract Background Cardiac magnetic resonance (CMR) characterization of myocardial tissue is routinely used in clinical practice. Compared to traditional CT, Photon counting CT (PCCT) uses photon-counting detectors offering higher spatial resolution, elimination of electronic noise and improved contrast-to-noise ratio. A comparison between CMR and PCCT for myocardial characterizazion in an urgent setting, however, has not yet been explored. Purpose The aim of this study was to compare the ability to characterize myocardial tissue between PCCT and CMR in patients presenting with acute chest pain in the emergency department (ED). Methods This single-center prospective study enrolled all consecutive patients presenting to the ED of our hospital from November 2023 to January 2024 with chest pain, ECG alterations and troponin rise consistent with myocardial injury. Patients needing urgent coronary angiography according to guidelines were excluded. PCCT was performed urgently for triple rule-out, but also for tissue characterization through post-iodine-contrast administration images. Within 24 hours, all patients underwent a CMR protocol including T2-weighted and late gadolinium enhancement (LGE) images for tissue characterization. Results Six male patients with a mean age of 20 ± 10 years were enrolled. All clinical, PCCT, and CMR parameters are presented in Table 1. All patients presented with diffuse ST-segment elevation and exhibited T2-weighted images (for edema detection) and LGE distribution (subepicardial and intramyocardial) consistent with acute myocarditis. Mean radiation exposure for PCCT was 0.8±0.1 mSv. A strong linear correlation emerged between PCCT-derived delayed enhancement (DE) volume and CMR-derived late gadolinium enhancement (LGE) volume (r = 0.970; p value 0.001) (Table 1). Similar results were achieved when comparing the number of DE and LGE myocardial segments (r = 0.871; p value 0.026). Significant correlations also emerged between DE, LGE, and high-sensitive troponin (hsTN) at presentation (respectively: PCCT-DE vs hsTN r = 0.951, p value 0.004; CMR-LGE vs hsTN r = 0.918, p value 0.010). CMR showed a much higher signal-to-noise ratio (SNR) for the delayed enhanced myocardium and contrast-to-noise (CNR) ratio between the delayed enhanced and normal myocardium with respect to PCCT in post-contrast images (respectively 7.4 ± 3.9 vs 27.2 ± 17.7, p value 0.024 and 5.5 ± 3.7 vs 38.8 ± 30.2, p value 0.023). In T2-weighted images both SNR for the hyperintense myocardium (30.3 [20.4-122.4]) and CNR between the hyperintense and normal myocardium (26.7 [13.3-60.2]) resulted to be higher compared to PCCT (p value 0.027 and 0.045, respectively) (Table 1). Conclusions PCCT appears to be reliable when compared to CMR for detecting myocardial edema through the acquisition of post-contrast images in the acute setting with an acceptable CNR.

Pediatric contrast-enhanced chest CT on a photon-counting detector CT: radiation dose and image quality compared to energy-integrated detector CT.

Photon counting detector (PCD) CT benefits from reduced noise compared with conventional energy-integrating detector (EID) CT, which should translate to improved image quality and reduced radiation exposure for pediatric patients undergoing chest CT with IV contrast. To determine the differences in radiation exposure and image quality of PCD CT and EID CT in pediatric chest CT with intravenous (IV) contrast. In this institutional review board-approved retrospective observational study, 20 scan pairs (20 PCD CT; 20 EID CT) for children who underwent chest CT with IV contrast on both a PCD CT (Siemens NAEOTOM Alpha) and an EID CT (Siemens SOMATOM Definition Edge or Force) within 12months were reviewed independently by three pediatric radiologists for three subjective quality features on 5-point Likert scales: overall quality, small structure delineation, and motion artifact. Objective measures of image quality (image noise, signal-to-noise ratio, and contrast-to-noise ratio) were assessed by a single radiologist in several locations in the chest through region of interest measurement of Hounsfield units (HU) and standard deviation. Patient-related and radiation exposure parameters were collected for each scan and summarized with median and interquartile range (IQR). The Wilcoxon rank-sum test was utilized to compare groups. A P < 0.05 indicated statistical significance. Inter-observer agreement of subjective image quality metrics was analyzed using weighted kappa. Age (14.2years vs 13.8years, P= 0.15), height (P= 0.13), weight (P= 0.21), and BMI (P = 0.24) did not significantly differ between groups. There were 10 male and 3 female patients. Compared to EID CT, PCD CT showed lower radiation exposure parameters including volumetric CT dose index, 1.7mGy (IQR 1.1-2.4mGy) vs 3.8mGy (IQR 2.0-4.7mGy) (P< 0.01), and size-specific dose estimate, 2.6mGy (IQR 1.8-3.1mGy) vs 5.0mGy (IQR 3.3-6.2mGy) (P< 0.01). Objective image quality of lung parenchyma was improved on the PCD CT scanner, including image noise 119.5 HU (IQR 95.4-135.7 HU) vs 143.1 HU (IQR 125.4-169.8 HU) (P < 0.01), signal-to-noise ratio (SNR) -6.1 (IQR -8.4 to -4.8) vs -4.9 (IQR -5.6 to -3.8) (P= 0.01), and contrast-to-noise ratio -63.9 (-84.1 to -57.5) vs -60.5 (-76.3 to -52.5) (P = 0.01). Motion artifact was improved on the PCD CT scanner (P< 0.01). No significant differences in overall image quality or small structure delineation were identified (P= 0.06 and P= 0.31). PCD CT pediatric chest CT had significantly reduced radiation exposure, improved image quality, and reduced motion artifact compared with EID CT.

Enhanced signal to noise ratio of single entity electrochemistry signal of platinum nanoparticles using passive silver ultramicroelectrode

AbstractThe single‐entity electrochemistry (SEE) of electrocatalytic platinum (Pt) single nanoparticles (NPs) on a less electrocatalytic silver (Ag) ultramicroelectrode (UME) surface was investigated using the electrocatalytic amplification method. Two characteristic types of current responses—current staircases and blips (or spikes)—were observed during single NP collision experiments, depending on the applied potential at the Ag UME. Notably, at applied potentials of 0.13 and 0.17 V, the Ag UME becomes passive due to the formation of a delicate oxide layer, resulting in a highly stable background current. This leads to an enhanced signal‐to‐noise (S/N) ratio, attributed to the low background current, when using Ag UME compared to commonly used UMEs such as Au, C, Ni, and Hg for the SEE of Pt NPs. The exceptionally low background current can provide a significant advantage for detailed observation of SEE signals and further mechanistic studies based on the current response.

Large vessel vasculitis evaluation by CTA: impact of deep-learning reconstruction and “dark blood” technique

ObjectivesTo assess the performance of the “dark blood” (DB) technique, deep-learning reconstruction (DLR), and their combination on aortic images for large-vessel vasculitis (LVV) patients.Materials and methodsFifty patients diagnosed with LVV scheduled for aortic computed tomography angiography (CTA) were prospectively recruited in a single center. Arterial and delayed-phase images of the aorta were reconstructed using the hybrid iterative reconstruction (HIR) and DLR algorithms. HIR or DLR DB image sets were generated using corresponding arterial and delayed-phase image sets based on a “contrast-enhancement-boost” technique. Quantitative parameters of aortic wall image quality were evaluated.ResultsCompared to the arterial phase image sets, decreased image noise and increased signal-noise-ratio (SNR) and CNRouter (all p < 0.05) were obtained for the DB image sets. Compared with delayed-phase image sets, dark-blood image sets combined with the DLR algorithm revealed equivalent noise (p > 0.99) and increased SNR (p < 0.001), CNRouter (p = 0.006), and CNRinner (p < 0.001). For overall image quality, the scores of DB image sets were significantly higher than those of delayed-phase image sets (all p < 0.001). Image sets obtained using the DLR algorithm received significantly better qualitative scores (all p < 0.05) in all three phases. The image quality improvement caused by the DLR algorithm was most prominent for the DB phase image sets.ConclusionDB CTA improves image quality and provides better visualization of the aorta for the LVV aorta vessel wall. The DB technique reconstructed by the DLR algorithm achieved the best overall performance compared with the other image sequences.Critical relevance statementDeep-learning-based “dark blood” images improve vessel wall image wall quality and boundary visualization.Key PointsDark blood CTA improves image quality and provides better aortic wall visualization.Deep-learning CTA presented higher quality and subjective scores compared to HIR.Combination of dark blood and deep-learning reconstruction obtained the best overall performance.Graphical

Research on frequency shift signal detection algorithm for jointless track circuits based on improved relaxation algorithm

The accuracy of ZPW-2000 frequency shift signal demodulation is related to the safety and efficiency of high-speed trains. This paper proposed a kind of ZPW-2000 frequency-shift signal detection algorithm based on improved Relaxation algorithm (ZFSD-IR) to address the issue of low accuracy in detecting ZPW-2000 frequency shift signal under strong noise interference, as the traditional fast Fourier transform (FFT) spectrum analysis methods are susceptible to fence effects and spectrum leakage effects. Firstly, the principle of ZPW-2000 jointless track circuit was analyzed, and then the ideal and simplified models of ZPW-2000 frequency shift signal were established, respectively. Finally, the simulation experiments were conducted on ZPW-2000 frequency shift signal detection under different sampling durations and signal-to-noise ratios (SNR). The effectiveness of the proposed algorithm was verified through comparative analysis with the traditional algorithms. The research results indicated that the ZFSD-IR algorithm has better accuracy in carrier-frequency and low-frequency estimation than traditional algorithms, and can achieve accurate detection of ZPW-2000 frequency shift signal under the lower SNR conditions. It has high detection accuracy and good anti-interference ability, ensuring the safe operation of high-speed trains.

In-Depth Analysis of Low-Cost Micro Electromechanical System (MEMS) Accelerometers in the Context of Low Frequencies and Vibration Amplitudes

Shock and vibration hazards to civil structures are common and come not only from earthquakes but most often from mining operations or foundation work involving the installation of piles using hammer-driving and vibrating technology. The purpose of this study is to present test methods for low-cost MEMS accelerometers in terms of their selection for low-amplitude acceleration vibration-prone object-monitoring systems. Tests of 24 commercially available digital accelerometers were carried out on a custom-built test bench, selecting four models for detailed tests conducted on a specially built precision vibration table capable of inflicting accelerations at frequencies of 1–2 Hz, using displacements as small as a few micrometers. The analysis of the results was based, among other things, on a modified method of determining the signal-to-noise ratio (SNR) and also on the idea of the effective number of bits (ENOB). The results of the analysis showed that among low-cost MEMS accelerometers, there are some that are successfully suitable for the monitoring and warning of excessive vibration hazards in situations where objects are extremely sensitive to such impacts (e.g., treatment rooms in hospitals). Examples of accelerometers capable of detecting harmonic vibrations with amplitudes as small as 10 mm/s2 or impulsive shocks with amplitudes of at least 70 mm/s2 are indicated.

Prospective 3D Fat Navigator (FatNav) motion correction for 7T Terra MRI.

Ultra-high field (7T) MRI allows scans at sub-millimetre resolution with exquisite signal-to-noise ratio (SNR). As 7T MRI becomes more widely used clinically, the challenge of patient motion must be overcome. Retrospective motion correction is used successfully for some protocols, but for acquisitions such as slice-by-slice scans only prospective motion correction can deliver the full potential of 7T MRI. We report the first implementation of prospective 3D Fat Navigator ("FatNav") motion correction for the Siemens 7T Terra MRI. We implemented a modular Sequence Building Block for FatNav and embedded it into the vendor's gradient-recalled echo (GRE) sequence. We modified the reconstruction pipeline to reconstruct FatNav images online, coregistering them and sending motion updates to the host sequence online. We tested five registration algorithms for performance and accuracy on synthetic FatNav data. We implemented the best three of these in our sequence and tested them online. We acquired T1 and T2* weighted brain images of healthy volunteers correcting every other image for motion to visualise the effectiveness of online motion correction. Data were acquired with and without head immobilisation. We also tested performance while correcting every measurement for motion. Our implementation uses a 1.23 s 3D FatNav acquisition module and delivers motion updates in less than 3s, which is sufficient for motion updates every few k-space lines in typical scans. Corrected images are crisper with fewer visible motion artefacts. This improved sharpness is reflected quantitatively by an increase in the variance of the image Laplacian which is 1.59 x better for corrected vs uncorrected images. Profiles across the cerebral falx are 33% steeper for corrected vs uncorrected images. Prospective FatNav improves GRE image quality in the brain. Our modular Sequence Building Block provides a simple method to integrate motion correction in 7T MRI pulse sequences.

Spectral Subtraction Based Weighted Function for Pitch Extraction in Noisy Speech

Many speech-related works employ the pitch period as a crucial component. Speech signals are typically collected in challenging noisy settings for real-world projects. Therefore, it is now more important than ever for the algorithm to be noise resistant in order to estimate pitch accurately. However, when dealing with noisy speech files at a low signal-to-noise ratio (SNR) value, many state-of-the-art algorithms are unable to produce satisfactory results. In this work, a new noise-resistant pitch estimation algorithm based on spectral subtraction is presented, which uses a weighted function to lessen the impact of the vocal tract effect. Furthermore, to enhance the correlation between the pitch estimates and smoothen the pitch contours, we employ a weighted function that combines the spectral subtraction-based technique as the numerator and the circular average magnitude difference function (CAMDF) as the denominator. We have utilized two noisy speech databases using seven different kinds of recorded ambient noise, and we evaluated our system against three cutting-edge methods. The suggested method lowers the Gross Pitch Error (GPE) rate at practically all SNRs in white noise and performs best on the NTT and KEELE databases.

Signature-based IaaS Performance Change Detection

We propose a novel change detection framework to identify changes in the long-term performance behavior of an IaaS service. An IaaS service’s long-term performance behavior is represented by an IaaS performance signature. The proposed framework leverages time series similarity measures and a sliding window technique to detect changes in IaaS performance signatures. We introduce a new IaaS performance noise model that enables the proposed framework to distinguish between performance noise and actual changes in performance. The proposed framework utilizes a novel Signal-to-Noise Ratio (SNR) based approach to detect changes when prior knowledge about performance noise is available. A set of experiments is conducted using real-world datasets to demonstrate the effectiveness of the proposed change detection framework.

Early clinical efficacy study on the efficacy of a three-stage conservative Chinese medicine external treatment for acute lateral ankle ligament injuries

To evaluate the clinical effect of a new three-phase Chinese medicine (CM) external treatment for acute lateral ankle ligament injuries. From July to December 2023, 64 patients with acute lateral ankle ligament injuries were randomly assigned to receive either the new three-phase CM external treatment combined with the POLICE(protect, optimal loading, ice, compression, elevation) treatment (observation group) or the POLICE treatment (control group), with 32 cases in each group. The observation group consisted of 17 males and 15 females, with an average age of(30.59±3.10) years old ranging from 25 to 36 years old, while the control group included 14 males and 18 females, with an average age of(30.03±3.19) years old ranging from 24 to 37 years old. Visual analogue scale (VAS) evaluation and Figure of 8 measurement were used to evaluate the degree of ankle joint pain and swelling of the subjects at the initial enrollment and after 1 week and sixth weeks of treatment. At the same time, the American Orthopaedic Foot and Ankle Society (AOFAS) and Karlsson Ankle Function Score System were used to evaluate the improvement of ankle joint function in patients at all stages. MRI imaging was employed to observe the degree of biological healing of the anterior talofibular ligament, with the signal to noise ratio(SNR) indicating the level of healing. A lower SNR suggests better ligament healing, as it represents lower water content in the ligament. All patients completed a 6-week follow-up. There was no significant difference in VAS, AOFAS score and Karlsson score between the two groups before treatment (P>0.05). After 1 week and 6 weeks of treatment, the VAS, AOFAS score and Karlsson score of the two groups were significantly improved (P<0.05). After 1 week of treatment, the VAS score of the observation group (3.21±0.87) was lower than that of the control group (4.21±1.50), and the difference was statistically significant (P<0.05). After 1 weeks of treatment, the AOFAS and Karlsson scores [(50.84±4.70) points, (49.97±4.00) points] of the observation group were higher than those [(46.91±5.56) points, (46.66±5.36) points]of the control group (P<0.05). MRI images showed that after 6 weeks of treatment, the SNR value of the observation group was significantly lower than that of the control group, and the difference was statistically significant(SNR of the observation group was 75.25±16.59, the contral gruop was 85.81±15.55), (P<0.05). Compared with the control group, the new three-phase CM external treatment is significantly effective in reducing pain and swelling, enhancing ligament repair quality, and promoting functional recovery of the ankle joint in patients with acute lateral malleolar ligament injuries.

Comparison of Subdural and Intracortical Recordings of Somatosensory Evoked Responses

Micro-electrocorticography (µECoG) electrodes have emerged to balance the trade-off between invasiveness and signal quality in brain recordings. However, its large-scale applicability is still hindered by a lack of comparative studies assessing the relationship between ECoG and traditional recording methods such as penetrating electrodes. This study aimed to compare somatosensory evoked potentials (SEPs) through the lenses of a µECoG and an intracortical microelectrode array (MEA). The electrodes were implanted in the pig’s primary somatosensory cortex, while SEPs were generated by applying electrical stimulation to the ulnar nerve. The SEP amplitude, signal-to-noise ratio (SNR), power spectral density (PSD), and correlation structure were analysed. Overall, SEPs resulting from MEA recordings had higher amplitudes and contained significantly more spectral power, especially at higher frequencies. However, the SNRs were similar between the interfaces. These results demonstrate the feasibility of using µECoG to decode SEPs with wide-range applications in physiology monitoring and brain–computer interfaces.

Deep learning-based super-resolution and denoising algorithm improves reliability of dynamic contrast-enhanced MRI in diffuse glioma

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to non-invasively image blood-brain barrier leakage, yet its clinical utility has been hampered by issues such as noise and partial volume artifacts. In this retrospective study involving 306 adult patients with diffuse glioma, we applied deep learning-based super-resolution and denoising (DLSD) techniques to enhance the signal-to-noise ratio (SNR) and resolution of DCE-MRI. Quantitative analysis comparing standard DCE-MRI (std-DCE) and DL-enhanced DCE-MRI (DL-DCE) revealed that DL-DCE achieved significantly higher SNR and contrast-to-noise ratio (CNR) compared to std-DCE (SNR, 52.09 vs 27.21; CNR, 9.40 vs 4.71; P < 0.001 for all). Diagnostic performance assessed by the area under the receiver operating characteristic curve (AUROC) showed improved differentiation of WHO grades based on a pharmacokinetic parameter \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {V}_{{e}}$$\\end{document} (AUC, 0.88 vs 0.83, P = 0.02), while remaining comparable to std-DCE in other parameters. Analysis of arterial input function (AIF) reliability demonstrated that \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {AIF}_{{DL}}$$\\end{document} exhibited superior agreement compared to \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {AIF}_{{std}}$$\\end{document}, as indicated by mostly higher intraclass correlation coefficients (Time to peak, 0.79 vs 0.43, P < 0.001). In conclusion, DLSD significantly enhances both the image quality and reliability of DCE-MRI in patients with diffuse glioma, while maintaining or improving diagnostic performance.