Signal-to-noise Ratio Measurements Research Articles

Motion robust coronary MR angiography using zigzag centric ky-kz trajectory and high-resolution deep learning reconstruction.

To develop a new MR coronary angiography (MRCA) technique by employing a zigzag fan-shaped centric ky-kz k-space trajectory combined with high-resolutiondeep learning reconstruction (HR-DLR). All imaging data were acquired from 12 healthy subjects and 2 patients using two clinical 3-T MR imagers, with institutional review board approval. Ten healthy subjects underwent both standard 3D fast gradient echo (sFGE) and centric ky-kz k-space trajectory FGE (cFGE) acquisitions to compare the scan time and image quality. Quantitative measures were also performed for signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) as well as sharpness of the vessel. Furthermore, the feasibility of the proposed cFGE sequence was assessed in two patients. For assessing the feasibility of the centric ky-kz trajectory, the navigator-echo window of a 30-mm threshold was applied in cFGE, whereas sFGE was applied using a standard 5-mm threshold. Image quality of MRCA using cFGE with HR-DLR and sFGE without HR-DLR was scored in a 5-point scale (non-diagnostic = 1, fair = 2, moderate = 3, good = 4, and excellent = 5). Image evaluation of cFGE, applying HR-DLR, was compared with sFGE without HR-DLR. Friedman test, Wilcoxon signed-rank test, or paired t tests were performed for the comparison of related variables. The actual MRCA scan time of cFGE with a 30-mm threshold was acquired in less than 5min, achieving nearly 100% efficiency, showcasing its expeditious and robustness. In contrast, sFGE was acquired with a 5-mm threshold and had an average scan time of approximately 15min. Overall image quality for MRCA was scored 3.3 for sFGE and 2.7 for cFGE without HR-DLR but increased to 3.6 for cFGE with HR-DLR and (p < 0.05). The clinical result of patients obtained within 5min showed good quality images in both patients, even with a stent, without artifacts. Quantitative measures of SNR, CNR, and sharpness of vessel presented higher in cFGE with HR-DLR. Our findings demonstrate a robust, time-efficient solution for high-quality MRCA, enhancing patient comfort and increasing clinical throughput.

Solid-State NMR 13C sensitivity at high magnetic field

Sensitivity is the foundation of every NMR experiment, and the signal-to-noise ratio (SNR) should increase with static (B0) magnetic field, by a proportionality that primarily depends on the design of the NMR probe and receiver. In the low B0 field limit, where the coil geometry is much smaller than the wavelength of the NMR frequency, SNR can increase in proportion to B0 to the power 7/4. For modern magic-angle spinning (MAS) probes, this approximation holds for rotor sizes up to 3.2 mm at 14.1 Tesla (T), corresponding to 600 MHz 1H and 151 MHz 13C Larmor frequencies. To obtain the anticipated benefit of larger coils and/or higher B0 fields requires a quantitative understanding of the contributions to SNR, utilizing standard samples and protocols that reproduce SNR measurements with high accuracy and precision. Here, we present such a systematic and comprehensive study of 13C SNR under MAS over the range of 14.1 to 21.1 T. We evaluate a range of probe designs utilizing 1.6, 2.5 and 3.2 mm rotors, including 24 different sets of measurements on 17 probe configurations using five spectrometers. We utilize N-acetyl valine as the primary standard and compare and contrast with other commonly used standard samples (adamantane, glycine, hexamethylbenzene, and 3-methylglutaric acid). These robust approaches and standard operating procedures provide an improved understanding of the contributions from probe efficiency, receiver noise figure, and B0 dependence in a range of custom-designed and commercially available probes. We find that the optimal raw SNR is obtained with balanced 3.2 mm design at 17.6 T, that the best mass-limited SNR is achieved with a balanced 1.6 mm design at 21.1 T, and that the raw SNR at 21.1 T reaches diminishing returns with rotors larger than 2.5 mm.

Repeatability of image quality in very low-field MRI.

Very low-field MR has emerged as a promising complementary device to high-field MRI scanners, offering several advantages. One of the key benefits is that very low-field scanners are generally more portable and affordable to purchase and maintain, making them an attractive option for medical facilities looking to reduce costs. Very low-field MRI systems also have lower RF power deposition, making them safer and less likely to cause tissue heating or other safety concerns. They are also simpler to maintain, as they do not require cooling agents such as liquid helium. However, these portable MR scanners are impacted by temperature, lower magnetic field strength, and inhomogeneity, resulting in images with lower signal-to-noise ratio (SNR) and higher geometric distortions. It is essential to investigate and tabulate the variations in these parameters to establish bounds so that subsequent in vivo studies and deployment of these portable systems can be well informed. The aim of this work is to investigate the repeatability of image quality metrics such as SNR and geometrical distortion at 0.05 T over 10 days and three sessions per day. We acquired repeatability data over 10 days with three sessions per day. The measurements included temperature, humidity, transmit frequency, off-resonance maps, and 3D turbo spin echo (TSE) images of an in vitro phantom. This resulted in a protocol with 11 sequences. We also acquired a 3 T data set for reference. The image quality metrics included computing SNR and eccentricity (to assess geometrical distortion) to investigate the repeatability of 0.05 T image quality. The image reconstruction included drift correction, k-space filtering, and off-resonance correction. We computed the experimental parameters' coefficient of variation (CV) and the resulting image quality metrics to assess repeatability. We have explored the impact of electromagnetic interference (EMI) on image quality in very low-field MRI. The investigation involved varying both the distance and amplitude of the EMI-producing coil from the signal generator to analyze their effects on image quality. The range of temperature measured during the study was within 1.5 °C. The off-resonance maps acquired before and after the 3D TSE showed similar hotspots and were changed mainly by a global constant. The SNR measurements were highly repeatable across sessions and over the 10 days, quantified by a CV of 6.7%. The magnetic field inhomogeneity effects quantified by eccentricity showed a CV of 13.7%, but less than 5.1% in two of the three sessions over 10 days. The use of conjugate phase reconstruction mitigated geometrical distortion artifacts. Temperature and humidity did not significantly affect SNR or mean frequency drift within the ranges of these environmental factors investigated. The EMI experiment showed that as the amplitude increased the SNR decreased, and concurrently the root mean square of the background increased with a rise in EMI amplitude or a reduction in distance. We found that humidity and temperature in the range investigated did not impact SNR or frequency. Based on the CV values computed session-wise and for the overall study, our findings indicate high repeatability for SNR and magnetic field homogeneity.

Application Value of a Novel Micro-Coil in High-Resolution Imaging of Experimental Mice Based on 3.0 T Clinical MR.

The clinical magnetic resonance scanner (field strength ≤ 3.0 T) has limited efficacy in the high-resolution imaging of experimental mice. This study introduces a novel magnetic resonance micro-coil designed to enhance the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), thereby improving high-resolution imaging in experimental mice using clinical magnetic resonance scanners. Initially, a phantom was utilized to determine the maximum spatial resolution achievable by the novel micro-coil. Subsequently, 12 C57BL/6JGpt mice were included in this study, and the novel micro-coil was employed for their scanning. A clinical flexible coil was selected for comparative analysis. The scanning methodologies for both coils were consistent. The imaging clarity, noise, and artifacts produced by the two coils on mouse tissues and organs were subjectively evaluated, while the SNR and CNR of the brain, spinal cord, and liver were objectively measured. Differences in the images produced by the two coils were compared. The results indicated that the maximum spatial resolution of the novel micro-coil was 0.2 mm. Furthermore, the subjective evaluation of the images obtained using the novel micro-coil was superior to that of the flexible coil (p < 0.05). The SNR and CNR measurements for the brain, spinal cord, and liver using the novel micro-coil were significantly higher than those obtained with the flexible coil (p < 0.001). Our study suggests that the novel micro-coil is highly effective in enhancing the image quality of clinical magnetic resonance scanners in experimental mice.

Performance Enhancement in a Few-Mode Rayleigh-Brillouin Optical Time Domain Analysis System Using Pulse Coding and LMD Algorithm

Rayleigh Brillouin optical time domain analysis (BOTDA) uses the backscattered Rayleigh light generated in the fiber as the probe light, which has a lower detection light intensity compared to the BOTDA technique. As a result, its temperature-sensing technology suffers from a low signal-to-noise ratio (SNR) and severe sensing unreliability due to the influence of the low probe signal and high noise level. The pulse coding and LMD denoising method are applied to enhance the performance of the Brillouin frequency shift detection and temperature measurement. In this study, the mechanism of Rayleigh BOTDA based on a few-mode fiber (FMF) is investigated, the principles of the Golay code and local mean decomposition (LMD) algorithm are analyzed, and the experimental setup of the Rayleigh BOTDA system using an FMF is constructed to analyze the performance of the sensing system. Compared with a single pulse of 50 ns, the 32-bit Golay coding with a pulse width of 10 ns improves the spatial resolution to 1 m. Further enhanced by the LMD algorithm, the SNR and temperature measurement accuracy are increased by 5.5 dB and 1.05 °C, respectively. Finally, a spatial resolution of 1.12 m and a temperature measurement accuracy of 2.85 °C are achieved using a two-mode fiber with a length of 1 km.

Development of a continuous classroom signal-to-noise ratio measurement system

A successful learning experience requires children to be able to hear what the teacher is saying. To that end, children need a high signal-to-noise ratio (SNR) or speech audibility to hear the teacher under background noise, but SNR in the classrooms may not always be favourable depending on the activities taking place during a school day. We propose a classroom acoustic measurement system to monitor the time-varying SNR under interactive teaching scenarios. Emulating a child listening to the speech made by a teacher, the system utilises two consumer-grade wireless microphones, one attached to the teacher and the other located where the children would be seated. The signal received by the teacher's microphone is used as a voice activity detector to indicate the presence of the teacher's voice or noise-only audio instances. Subsequently, the children's microphone observes these instances to monitor the average classroom noise and estimate the resulting SNR. A pilot study was conducted at a primary school in Auckland, New Zealand where the SNR measurements were recorded and matched against behavioural coding of the classroom activities. Results show a reasonable agreement of the SNR to the activities performed under real-life classroom teaching scenarios.

Laser Heterodyne Detection Based on Photon Time–Domain Differential Detection Avoiding the Effect of Decoherence Phase Noise

Laser heterodyne detection (LHD) is a key velocimetry technique that provides better accuracy and sensitivity than direct laser detection. However, random phase noise can be introduced by the surface topography of the moving target undulation or atmospheric turbulence during transmission. The random phase noise causes the target echo to undergo decoherence, resulting in degradation of the signal-to-noise ratio (SNR). Here, we propose a novel LHD method based on photon time–domain differential detection. It can infer the heterodyne spectrum of the target echo and the local oscillator light from the time intervals of the photon arrival. The time interval statistic is a relative quantity, which can effectively avoid the effect of random phase noise in LHD. With our method, the SNR of LHD can be improved in application scenarios where the target echo is decoherent. We developed a complete solution model for acquiring the heterodyne spectrum based on photon time–domain differential detection and performed proof-of-principle experiments. The experimental results show that in the presence of random phase noise, the SNR and velocity measurement error of our method are significantly better than that of the conventional method, and the larger the phase noise is, the more the SNR and velocity measurement error of our method are improved. Moreover, along with the increase in phase noise, the SNR of our method is basically unchanged, which also indicates that our method is not affected by random phase noise. This advantage is significant for photon-level weak echoes that require long detection times to be detected.

Influence of wavefront distortion on the measurement of pulse signal-to-noise ratio

The high-fidelity measurement of the ultra-short and ultra-intense laser pulses' temporal signal-to-noise ratio (SNR) is of great significance. To the best of our knowledge, few studies have investigated the influence of wavefront distortion on the measurement of pulse SNR. In this work, a numerical model is constructed to study how wavefront distortion affects the measurement of ultra-short and ultra-intense pulse SNR by the single-shot third-order auto-correlation (TOAC) method. The nonlinear coupled-wave equations with wavefront distortion have been solved numerically by the split-step Fourier method and the fourth-order Runge-Kutta numerical algorithm. The wavefront distortion of the under-test fundamental wave will be transmitted to the second harmonic and third harmonic, leading to the phase mismatch in the second harmonic generation (SHG) and third harmonic generation (THG), further resulting in the deterioration of the measured SNR. We analyze the influence of different spatial frequencies and peak-to-valley (PV) values on the measurements of SNR. The larger the spatial frequency or PV value of the wavefront distortion, the more severe the degradation of the SNR.

Enhancing QoS Performance for Cell Edge Users Through Adaptive Modulation and Coding in IEEE 802.11ac WLANs

Wireless communication networks, such as IEEE 802.11ac Wireless Local Area Networks (WLANs), often encounter challenges in providing consistent Quality of Service (QoS) to users situated at the cell edge. The inherent variations in channel conditions, particularly lower signal-to-noise ratios (SNRs) in these regions, lead to compromised data rates and reliability, resulting in significant degradation of throughput. This study presents an innovative solution in the form of an Adaptive Modulation and Coding Scheme (AMCS) algorithm tailored to enhance QoS performance for cell edge users. The primary objective of the AMCS algorithm is to optimize QoS by dynamically adjusting the transmission data rate based on the observed channel conditions, quantified using SNR as a channel state indicator. Conventional approaches might unilaterally select the lowest data rate in challenging conditions, prioritizing reliability at the expense of throughput. However, the proposed AMCS algorithm takes a distinct approach by intelligently determining the Modulation and Coding Scheme (MCS) that offers an optimal balance between throughput and reliability for the given SNR level. To achieve this, the algorithm utilizes real-time SNR measurements to select an MCS that ensures a stable connection while also maintaining an acceptable data rate. By adapting the MCS based on the current SNR, the algorithm aims to mitigate the adverse effects of poor channel conditions experienced by cell edge users. The innovation of the AMCS algorithm lies in its ability to make dynamic adjustments, allowing users to experience improved data rates without compromising connection stability. Through extensive simulations and evaluations, the proposed AMCS algorithm showcases its efficacy in enhancing QoS performance at the cell edge. The algorithm's adaptive approach successfully achieves higher data rates and improved reliability by selecting appropriate MCS configurations tailored to the observed SNR levels. This innovative technique provides a promising solution to the challenge of striking the right balance between throughput and reliability in wireless communication networks, ultimately leading to an improved user experience for those at the network's periphery.

Quality assurance and temporal stability of a 1.5 T MRI scanner for MR-guided Photon and Particle Therapy

PurposeTo describe performance measurements, adaptations and time stability over 20 months of a diagnostic MR scanner for integration into MR-guided photon and particle radiotherapy. Material and methodsFor realization of MR-guided photon and particle therapy (MRgRT/MRgPT), a 1.5 T MR scanner was installed at the Heidelberg Ion Beam Therapy Center. To integrate MRI into the treatment process, a flat tabletop and dedicated coil holders for flex coils were used, which prevent deformation of the patient external contour and allow for the use of immobilization tools for reproducible positioning. The signal-to-noise ratio (SNR) was compared for the diagnostic and therapy-specific setup using the flat couch top and flexible coils for the a) head & neck and b) abdominal region as well as for different bandwidths and clinical pulse sequences. Additionally, a quality assurance (QA) protocol with monthly measurements of the ACR phantom and measurement of geometric distortions for a large field-of-view (FOV) was implemented to assess the imaging quality parameters of the device over the course of 20 months. ResultsThe SNR measurements showed a decreased SNR for the RT-specific as compared to the diagnostic setup of (a) 26% to 34% and (b) 11% to 33%. No significant bandwidth dependency for this ratio was found. The longitudinal assessment of the image quality parameters with the ACR and distortion phantom confirmed the long-term stability of the MRI device. ConclusionA diagnostic MRI was commissioned for use in MR-guided particle therapy. Using a radiotherapy specific setup, a high geometric accuracy and signal homogeneity was obtained after some adaptions and the measured parameters were shown to be stable over a period of 20 months.

Acquisition time reduction of diffusion-weighted liver imaging using deep learning image reconstruction.

The purpose of this study was to investigate the impact of deep learning accelerated diffusion-weighted imaging (DWIDL) in 1.5-T liver MRI on image quality, sharpness, and diagnostic confidence. One-hundred patients who underwent liver MRI at 1.5-T including DWI with two different b-values (50 and 800s/mm²) between February and April 2022 were retrospectively included. There were 54 men and 46 women, with a mean age of 59±14 (SD) years (range: 21-88 years). The single average raw data were retrospectively processed using a deep learning (DL) image reconstruction algorithm leading to a simulated acquisition time of 1min 28s for DWIDL as compared to 2min 31s for standard DWI (DWIStd) via reduction of signal averages. All DWI datasets were reviewed by four radiologists using a Likert scale ranging from 1-4 using the following criteria: noise level, extent of artifacts, sharpness, overall image quality, and diagnostic confidence. Furthermore, quantitative assessment of noise and signal-to-noise ratio (SNR) was performed via regions of interest. No significant differences were found regarding artifacts and overall image quality (P>0.05). Noise measurements for the spleen, liver, and erector spinae muscles revealed significantly lower noise for DWIDL versus DWIStd (P<0.001). SNR measurements in the above-mentioned tissues also showed significantly superior results for DWIDL versus DWIStd for b=50s/mm² and ADC maps (all P<0.001). For b=800s/mm², significantly superior results were found for the spleen, right hemiliver, and erector spinae muscles. DL image reconstruction of liver DWI at 1.5-T is feasible including significant reduction of acquisition time without compromised image quality.

Evaluation of the Influence of Body Mass Index and Signal-to-Noise Ratio on the PET/CT Image Quality in Iraqi Patients with Liver Cancer

Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviation. We obtained the liver's Signal-to-Noise Ratio from the ratio of both. Weight, height, SNR, and Body Mass Index were determined using a spreadsheet, and graphs were created to show the relationship between these variables. The graphs demonstrated that SNR decreases when BMI increases and that, despite an increase in injection dose, SNR also decreases. This is because heavier individuals take higher doses and, according to reports, have lower SNR. These results show that, despite receiving larger FDG doses, heavier patients' images, as measured by SNR, are of lower quality than thinner patients' images.&#x0D;

Perceptual and objective physical quality of chest images: a comparison between digital radiographic chest images processed for cancer screening and pneumoconiosis screening in Japan.

This study (1) evaluated the perceptual and objective physical quality of digital radiographic chest images processed for different purposes (routine hospital use, lung cancer screening, and pneumoconiosis screening), and (2) quantified objectively the quality of chest images visually graded by the Japan National Federation of Industrial Health Organization (ZENEIREN). Four observers rated the images using a visual grading score (VGS) according to ZENEIREN's quality criteria. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured. Between groups, differences were assessed using ANOVA (followed by Bonferroni multiple comparisons) or unpaired t-test. The Pearson's correlation coefficients were calculated for the correlation between perceptual quality and objective physical image quality. The image quality perceived by the observers and the SNR measurements were highest for the images generated using parameters recommended for lung cancer screening. The images processed for pneumoconiosis screening were rated poorest by the observers and showed the lowest objective physical quality measurements. The chest images rated high quality by ZENEIREN generally showed a higher objective physical image quality. The SNR correlated well with VGS, but CNR did not. Highly significant differences between the processing parameters indicate that image processing strongly influences the perceptual quality of digital radiographic chest images.

An Improved Method to Enhance SNR of Non-Stationary Signal Based on Nonuniform Windows Adaptive Modulation for Measurement

It is very important for non-stationary signal processing, signal measurement, and signal enhancement to improve signal-to-noise ratio (SNR) and suppress noise. For complex non-stationary signals measurement, there is still a lack of effective methods to improve the signal-to-noise ratio without damaging original signal. Therefore, it is vital to develop signal processing method to improve SNR of non-stationary signal in many actual industrial measurement. This paper proposes a new method to enhance the SNR for non-stationary signal processing. First, a self-adapting mathematic model is presented to describe the short-time impulse with board spectrum, judge the non-stationary part of the signal, and determine the length of time window based on itself. Then, for the non-stationary signals in this short time window, the improved self-adaptive modulation is used to remove the non-stationary components and retain the stationary components. Third, the stationary component of the short-time window and the normal part of the original signal are connected via cubic spline interpolation algorithm. Finally, this paper analyzes the range of SNR improvement and measurement accuracy of the new method. Based on the results of experiment, the proposed method can effectively improve the signal-to-noise ratio of non-stationary signals and suppress noise, which is of great significance for measurement.

Signal-to-noise ratio penalties from a loss of stimulated echoes when using slab-selective excitation in three-dimensional fast spin echo imaging with long echo trains.

Three-dimensional fast spin echo imaging with long echo trains combines high resolution with reasonable acquisition times and reduced specific absorption rate due tolow refocusing flip angles. Typically, an entire volume is encoded (nonselective excitation) or localization can be performed with slab select excitation, which uses a long 90° pulse for precise localization, followed by a preliminary nonselective 180° pulse bounded by spoiler gradients to destroy signal outside of the volume of interest. Subsequent flip angles in the train are nonselective and identical between the two methods. The inclusion of the initial selective pulse and spoiler gradients results in a signal-to-noise ratio (SNR) penalty for slab selection, beyond the slice-averaging dependence, arising from a loss of stimulated echoes. SNR differences are explored using Bloch equation simulations of a T2-weighted 96 echo train sequence with varying parameters including T2, T1, and B1+ and compared with phantom and in vivo brain, neck, and knee experiments. In vivo SNR measurements in the three regions showed a maximum decrease of selective SNR by 29% (gastrocnemius muscle), 25% (pons), and 22% (globus pallidus), despite similar experimental parameters to nonselective experiments. Decreased SNR was compounded by B1+ variation affecting prescribedflip angles with further smaller reductions with T2 and T1 times. In conclusion, the elimination of coherences via the preliminary nominal 180° pulse and spoiler gradients in addition to the extended echo timing from the long excitation pulse resulted in a reduction in SNR compared with the nonselective case. Consideration of the required SNR and chosen anatomy as well as sequence restrictions should be weighed before choosing slab-selective excitation.

Multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE) in diffusion-weighted imaging for rectal MRI: a quantitative and qualitative analysis at multiple b-values.

To compare four diffusion-weighted imaging (DWI) sequences for image quality, rectal contour, and lesion conspicuity, and to assess the difference in their signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC). In this retrospective study of 36 consecutive patients who underwent 3.0T rectal MRI from January-June 2020, DWI was performed with single-shot echo planar imaging (ss-EPI) (b800 s/mm2), multiplexed sensitivity encoding (MUSE) (b800 s/mm2), MUSE (b1500 s/mm2), and field-of-view optimized and constrained undistorted single-shot (FOCUS) (b1500 s/mm2). Two radiologists independently scored image quality using a 5-point Likert scale. Inter-reader agreement was assessed using the weighted Cohen's к. SNR, CNR, and ADC measurements were compared using the paired t-test. For both readers, MUSE b800 scored significantly higher for image quality, rectal contour, and lesion conspicuity compared to ss-EPI; MUSE b800 also scored significantly higher for image quality and rectal contour compared to all other sequences. Lesion conspicuity was equally superior for MUSE b800 and MUSE b1500 compared to the other two sequences. There was good to excellent inter-reader agreement for all qualitative features (к = 0.72-0.88). MUSE b800 had the highest SNR; MUSE b1500 had the highest CNR. A significant difference in ADC was observed between ss-EPI compared to the other sequences (p < 0.001) and between MUSE b800 and FOCUS. No significant difference in ADC was found between MUSE b1500 and FOCUS b1500. MUSE b800 improved image quality over ss-EPI and both MUSE b800 and b1500 showed better tumor conspicuity compared to conventional ss-EPI.

Convolutional neural network transformer (CNNT) for free-breathing real-time cine imaging

Abstract Funding Acknowledgements Type of funding sources: None. Background Real-time cine imaging does not require breath-holding and is a robust cine imaging technique in the presence of irregular heartbeats. It is a good alternative to the conventional breath-hold retro-gated cine for simplified acquisition and improved patient comfort. Real-time acquisition is achieved with the single-shot BSSFP readout without retro-gating. To maintain good temporal and spatial resolution, higher acceleration (e.g. &amp;gt;4x parallel imaging) is required. As a result, the real-time cine images experience reduced signal-to-noise ratio (SNR), which limits its clinical acceptance. Purpose We developed a novel deep learning model architecture, the Convolutional Neural Network Transformer (CNNT), to improve the quality of real-time cine, under 4x, 5x and 6x acceleration. Method Convolutional Neural Networks (CNN) are widely used in CMR research to process cardiac images. Cardiac images are often acquired as a time series with strong inter-phase correlation. We combined the CNN with the more recent transformer model to develop a novel CNNT architecture. It takes in the entire 2D+T time series as input and has advantages of CNN for efficient computation and spatial invariance. It further inherits the advantages of attention layer in the transformer and is able to efficiently utilize the temporal correlation within a time series. A CNNT model is developed to improve the SNR of real-time cine imaging. N=10 patients were scanned at a heart center, with 4x, 5x and 6x acceleration. Typical imaging parameters are: FOV 360×270mm2, flip angle 50°, acquired matrix size 160×90 for R=4 acceleration, 192×108 for R=5 and 6, temporal resolution 40ms for R=4, 42ms for R=5 and 35ms for R=6. The real-time images went through a TGRAPPA reconstruction [1] and the CNNT model. The SNR of TGRAPPA was measured with SNR units [2]. The Monte-Carlo pseudo-replica test was used to measure SNR for the CNNT model. For every cine series, two phases were picked for the end-systole and end-diastole. For every image picked, two region-of-interests were drawn in the myocardium and in the LV blood pool. The CNNT model was deployed inline on the MR scanner using the Gadgetron InlineAI [3]. Results Figure 1 gives real-time cine images for three accelerations, reconstructed with TGRAPPA and CNNT. The parallel imaging TGRAPPA reconstruction suffers significant SNR loss from elevated g-factor and less acquired data. The deep learning CNNT model recovered SNR even at the very high 6x acceleration, without observed loss of boundary sharpness. Table 1 lists the SNR measurement results. The TGRAPPA SNR decreased ∼4x from R=4 to R=6 for both the blood and myocardium. For the blood, the CNNT increased the SNR by 170%, 335%, 371% at R=4, 5 and 6. For the myocardium, the SNR increases were 335%, 634% and 828%. Conclusion We developed a convolutional neural network transformer model to recover the SNR for real-time cine imaging at higher acceleration.

Signal-to-noise ratio improvements in microwave-assisted laser-induced breakdown spectroscopy

A microwave-assisted laser-induced breakdown spectroscopy (MA-LIBS) was developed to enhance the signal-to-noise ratio (SNR) measurements of alumina oxide plates. A semiconductor-based 2.45 GHz microwave device was coupled to a semiconductor 1064 nm laser source using a helical antenna, which replaced the larger-size capacitor-like antenna. This work was motivated by the applications of laser-induced breakdown spectroscopy (LIBS) in decommissioning of Fukushima Daiichi Nuclear Power Station (FDNPS). When using a 50-meter optical fiber from the main source into the nuclear vessel, the LIBS laser energy was expected to decrease significantly. Using the low laser energy of equal to or less than 2.0 mJ, the MA-LIBS significantly enhanced the excitation of the neutrals of Aluminum (Al) and the background signals contained no continuum emissions. Significant increase of the emission intensities of Al I with the addition of microwave energy was observed which also increased the full-width-half-maximum (FWHM). The correlation of the laser and microwave parameters and the SNR were then analyzed. Results show the logarithmic correlation of the microwave pulse width and microwave energy to the intensity enhancement and SNR which is attributed to the absorption of the microwave energy. This correlation is consistent with variations of laser energy density, laser pulse number, and laser spot diameter. Using a delayed acquisition time, the emission intensities of Al I were only observed with the addition of microwaves. At the experimental threshold of laser breakdown energy using 0.3 mJ, the emission intensity of Al I was only observed with the addition of microwaves. Attempts to duplicate the same SNR measurements using the stainless steel and lead targets were also done. The microwave successfully enhanced the intensity emission and SNR of the Al I, Cr I, and Pb I excited species.

A Correlational Analysis between Audiometric Pure-tone Averages and Distortion Product Otoacoustic Emissions.

Hearing loss severely affects human speech communication and the quality of life, and efficient hearing screening can help hearing function diagnosis and subsequent hearing rehabilitation. Pure-tone audiometry test and distortion-product otoacoustic emission (DPOAE) measurement are two commonly-used clinical techniques for hearing loss diagnosis, and they were developed based on different mechanisms in a hearing process. Early work investigated the relation between audiometric thresholds and DPOAE measurements. The present work aimed to use a simple linear fitting to estimate audiometric pure-tone threshold averages (PTAs) from DPOAE signal-to-noise-ratio (SNR) measurements, i.e., DPOAE amplitude minus the mean noise floor. Audiometric PTA values and DPOAE SNRs were measured from both ears of 30 listeners with normal hearing or mild-to-moderate hearing loss. The DPOAE SNR measurements of 4 distortion products (i.e., 2fl-f2= 1, 2, 4 and 8 kHz) were combined with a linear prediction model, and correlated with the PTA values. Data analysis showed moderate high correlation coefficients (i.e., r=0.84 and 0.64) for the left and right ears, respectively. The results of the present work demonstrate the possibility to estimate the behavioral audiometric PTA values from the objective DPOAE SNR measurements for hearing loss diagnosis.

Improved detection of multiple sclerosis lesions with T2-prepared double inversion recovery at 3T.

Background and PurposeDouble inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal‐to‐noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.MethodsDIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2‐preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.ResultsDIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.ConclusionsDIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.