Signal-to-noise Ratio Values Research Articles

Research on super resolution angle measurement based on esprit algorithm

With the rapid development of communication, radar, sonar and many other fields, angle measurement has become a very important field in signal processing. Super resolution angle measurement, compared with the traditional angle measurement, has more advantages in accuracy, so it is widely used in practical production. Super resolution angle measurement includes MUSIC algorithm and ESPRIT algorithm. This paper firstly compares the MUSIC algorithm and ESPRIT algorithm, then elaborates the ESPRIT algorithm and deduces the process. In this paper, DOA estimation based on ESPRIT algorithm is carried out for three different number of input signal sources, and the errors are analysed according to different SNR (signal to noise ratio) values. Finally, based on the simulation results, the effectiveness of ESPRIT algorithm is evaluated.

Carotid artery perivascular adipose tissue on magnetic resonance imaging: a potential indicator for carotid vulnerable atherosclerotic plaque.

Magnetic resonance imaging (MRI) has the potential in assessing the inflammation of perivascular adipose tissue (PVAT) due to its excellent soft tissue contrast. However, evidence is lacking for the association between carotid PVAT measured by MRI and carotid vulnerable atherosclerotic plaques. This study aimed to investigate the association between signal intensity of PVAT and vulnerable plaques in carotid arteries using multi-contrast magnetic resonance (MR) vessel wall imaging. In this cross-sectional study, a total of 104 patients (mean age, 64.9±7.0 years; 86 men) with unilateral moderate-to-severe atherosclerotic stenosis referred to carotid endarterectomy (CEA) were recruited from April 2018 to December 2020 at Department of Neurosurgery of Peking University Third Hospital. All patients underwent multi-contrast MR vessel wall imaging including time-of-flight (ToF) MR angiography, black-blood T1-weighted (T1w) and T2-weighted (T2w) and simultaneous non-contrast angiography and intraplaque hemorrhage (IPH) imaging sequences. Patients with contraindications to endarterectomy or MRI examinations were excluded. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of PVAT were measured on ToF images and vulnerable plaque characteristics including IPH, large lipid-rich necrotic core (LRNC), and fibrous cap rupture (FCR) were identified. The SNR and CNR of PVAT were compared between slices with and without vulnerable plaque features using Mann-Whitney U test and their associations were analyzed using the generalized linear mixed model (GLMM). Carotid artery slices with IPH (30.93±14.56 vs. 27.34±10.02; P<0.001), FCR (30.35±13.82 vs. 27.53±10.37; P=0.006), and vulnerable plaque (29.15±12.52 vs. 27.32±10.05; P=0.016) had significantly higher value of SNR of PVAT compared to those without. After adjusting for clinical confounders, the SNR of PVAT was significantly associated with presence of IPH [odds ratio (OR) =0.627, 95% confidence interval (CI): 0.465-0.847, Puncorr=0.002, PFDR=0.016] and vulnerable plaque (OR =0.762, 95% CI: 0.629-0.924, Puncorr=0.006, PFDR=0.020). However, no significant association was found between the CNR of PVAT and presence of vulnerable plaque features (all P>0.05). The SNR of carotid artery PVAT measured by ToF MR angiography is independently associated with vulnerable atherosclerotic plaque features, suggesting that the signal intensity of PVAT might be an effective indicator for vulnerable plaque.

Re‐evaluating the choice of gamma stimulation frequency for potential treatment of Alzheimer’s disease: Novel invisible spectral flicker evokes gamma responses at various frequencies

AbstractBackgroundWith recent advances in the potential usage of visual gamma stimulation at 40 Hz for treatment of Alzheimer’s disease, there is reason to evaluate the use of other low gamma frequencies. The choice of 40 Hz is based on studies that describe “40 Hz” oscillations with considerable frequency variability. Results are also ambiguous on the acute effects of varying the frequency when stimulating with stroboscopic flicker in the low gamma range (30‐50 Hz). As stroboscopic visual stimulation may also affect adherence in clinical trials due to its inherent flickering, invisible spectral flicker (ISF) was proposed as a more comfortable alternative for entraining 40 Hz. This study investigates the ability of ISF to entrain gamma responses at several frequencies in the range of 36‐44 Hz.MethodTwenty healthy young volunteers were included in an electroencephalography (EEG) experiment (DTU Compute IRB Approval: COMP‐IRB‐2021‐01) with an initial eyes‐open baseline recording followed by a stimulation paradigm using ISF at nine different frequencies (36‐44 Hz, 1 Hz interval) in a randomized complete block design with five blocks. The responses were evaluated as the signal‐to‐noise ratio (SNR) averaged over the O1 and O2 electrodes at the stimulation frequency and analysed using mixed‐effect models with frequency as a fixed factor and subject and block as random factors. All two‐way interactions were included as random factors. Evoked responses were compared to baseline and between frequencies post hoc, correcting for multiple comparisons with Tukey’s method.ResultThe EEG power (Figure 1) showed that stimulus SNR values were significantly higher than baseline for all frequencies (P&lt;.05, see Figure 2), but no stimuli resulted in significantly different SNR. There was significant subject effect (P&lt;&lt;.05), and one subject responded 1‐2 orders of magnitude higher than the others. This suggests higher variability between subjects than frequencies alone.ConclusionOur results indicate that ISF can induce steady‐state visually evoked potentials at several frequencies in the low gamma range of 36‐44 Hz. Across the population of participants, we found no preference or trend for any specific gamma stimulation frequency in the tested range.

Neural Networks Push the Limits of Luminescence Lifetime Nanosensing.

Luminescence lifetime-based sensing is ideally suited to monitor biological systems due to its minimal invasiveness and remote working principle. Yet, its applicability is limited in conditions of low signal-to-noise ratio (SNR) induced by, e.g., short exposure times and presence of opaque tissues. Herein this limitation is overcome by applying a U-shaped convolutional neural network (U-NET) to improve luminescence lifetime estimation under conditions of extremely low SNR. Specifically, the prowess of the U-NET is showcased in the context of luminescence lifetime thermometry, achieving more precise thermal readouts using Ag2 S nanothermometers. Compared to traditional analysis methods of decay curve fitting and integration, the U-NET can extract average lifetimes more precisely and consistently regardless of the SNR value. The improvement achieved in the sensing performance using the U-NET is demonstrated with two experiments characterized by extreme measurement conditions: thermal monitoring of free-falling droplets, and monitoring of thermal transients in suspended droplets through an opaque medium. These results broaden the applicability of luminescence lifetime-based sensing in fields including in vivo experimentation and microfluidics, while, hopefully, spurring further research on the implementation of machine learning (ML) in luminescence sensing.

A novel energy efficient IRS-relay network for ITS with Nakagami-m fading channels

In this paper, we have investigated the performance of energy efficiency (EE) for Intelligent Transportation Systems (ITS), which recently emerged and advanced to preserve speed as well as safe transportation expansion via a cooperative IRS-relay network. To improve the EE, the relay model has been integrated with an IRS block consisting of a number of passive reflective elements. We analyze the ITS in terms of EE, and achievable rate, with different signal-to-noise ratio (SNR) values under Nakagami-m fading channel conditions that help the system to implement in a practical scenario. From the numerical results it is noticed that the EE for the only relay, IRS, and proposed cooperative relay-IRS-aided network at SNR value of 100 dBm is 30, 17, and 48 bits/joule respectively. In addition, we compare the impact of multi-IRS with the proposed cooperative IRS-relay and conventional relay-supported ITS. Simulation results show that both the proposed cooperative IRS-relay-aided ITS network and multi-IRS-aided network outperform the relay-assisted ITS with the increase in SNR.

Effects of Body Position on Cochlear Function in Infants: An Otoacoustic Emission Study.

Otoacoustic Emission (OAE) is frequently recorded in various body positions for infants. However, little is available about whether these deviations will produce non-pathological effects on the clinical results. The current study assessed body position's effect on infants' inner ear function. Sixty normally hearing infants participated in an analytical cross-sectional study. Distortion-product OAEs (DPOAEs) were measured in the supine, side-lying, and upright positions. The DPOAE amplitude and signal-to-noise ratio (SNR) were recorded across the 1500 to 6000Hz range. The mean DPOAE amplitude and SNR values were significantly greater in the upright position than supine and side-lying positions (p < 0.05). These differences were more pronounced in the 3000 to 6000Hz range. The effects of gender and ear asymmetry on DPOAEs were not statistically significant. Our findings suggested that the upright position could be regarded as the best position for assessing DPOAEs in infants.

Determination of Efficiency of 3D Fluid-Attenuated Inversion Recovery (FLAIR) in the Imaging of Multiple Sclerosis in Comparison With 2D FLAIR at 3-Tesla MRI.

A fluid-attenuated inversion recovery (FLAIR) method eliminates the cerebrospinal fluid (CSF) signal, enhancing white matter lesion detection by enhancing the contrast between the lesion and CSF. Three-dimensional (3D) volume acquisition has the advantage of multiplanar reformation of contiguous slices yielding improved signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs). To our knowledge, there are only three studies comparing 3D- and 2D-FLAIR sequences with respect to multiple sclerosis (MS) lesions at 3 tesla. This study aimed to determine the efficiency of 3D-FLAIR in the detection of lesions of multiple sclerosis in terms of spatial and contrast resolutions in comparison with 2D-FLAIR sequences. A total of 75 patients with MS undergoing magnetic resonance imaging (MRI) brain at the Department of Radiology, Krishna Institute of Medical Sciences (KIMS), Secunderabad, Telangana, India. This is an observational comparative study. Independent-samples t-tests were performed in the present study to compare the number of lesions detected. The measured CNR and SNR values were subjected to Mann-Whitney U test. As a result of the 3D-FLAIR, more lesions were found as compared to 2D-FLAIR (p = 0.001). There was a greater CNRs for 3D-FLAIR images than for 2D-FLAIR images (p = 0.001). Lesions, CSF, white matter, and gray matter showed significantly higher SNRs with 3D-FLAIR (p = 0.001). 3D-FLAIR has exhibited greater sensitivity in detecting lesions associated with MSwhen contrasted with the 2D-FLAIR sequence. Significantly more lesions and higher SNRs and CNRs were detected with 3D-FLAIR in contrast to 2D-FLAIR. 3D-FLAIR may be considered the sequence of choice for MS imaging in the future.

Lock-In Thermography with Cooling for the Inspection of Composite Materials.

This paper presents the development of the lock-in thermography system with an additional cooling system. System feasibility is tested by investigating a square-shaped glass fiber-reinforced polymer (GFRP) with artificially made outer flaws. The influence of heating mode and sinusoidal excitation period on the defect detectability is considered. Thus, the experiment is split into two modes: the sample is solely heated in the first mode or simultaneously heated and cooled in the second. In each mode, the temperature measurement is performed first with a shorter excitation signal period and second with a longer one. The signal-to-noise ratio (SNR) is used to assess defect detection quantitatively. The comparative analysis shows that employing a mixed heating-cooling mode improves the SNR compared to the conventional heating mode. The further enhancement of the SNR is obtained by extending the excitation period. The combination of simultaneous heating and cooling with longer periods of the excitation signal allows for the best SNR values for the most detected defects.

Deep Learning Image Reconstruction Algorithm for CCTA: Image Quality Assessment and Clinical Application.

The increasing number of coronary computed tomography angiography (CCTA) requests raised concerns about dose exposure. New dose reduction strategies based on artificial intelligence have been proposed to overcome limitations of iterative reconstruction (IR) algorithms. Our prospective study sought to explore the added value of deep-learning image reconstruction (DLIR) in comparison with a hybrid IR algorithm (adaptive statistical iterative reconstruction-veo [ASiR-V]) in CCTA, even in clinical challenging scenarios, as obesity, heavily calcified vessels and coronary stents. We prospectively included 103 consecutive patients who underwent CCTA. Data sets were reconstructed with ASiR-V and DLIR. For each reconstruction signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) was calculated, and qualitative assessment was made with a four-point Likert scale by two independent and blinded radiologists with different expertise. Both SNR and CNR were significantly higher in DLIR (SNR-DLIR median value [interquartile range] of 13.89 [11.06-16.35] and SNR-ASiR-V 25.42 [22.46-32.22], P < 0.001; CNR-DLIR 16.84 [9.83-27.08] vs CNR-ASiR-V 10.09 [5.69-13.5], P < 0.001).Median qualitative score was 4 for DLIR images versus 3 for ASiR-V ( P < 0.001), with a good interreader reliability [intraclass correlation coefficient(2,1)e intraclass correlation coefficient(3,1) 0.60 for DLIR and 0.62 and 0.73 for ASiR-V].In the obese and in the "calcifications and stents" groups, DLIR showed significantly higher values of SNR (24.23 vs 11.11, P < 0.001 and 24.55 vs 14.09, P < 0.001, respectively) and CNR (16.08 vs 8.04, P = 0.008 and 17.31 vs 10.14, P = 0.003) and image quality. Deep-learning image reconstruction in CCTA allows better SNR, CNR, and qualitative assessment than ASiR-V, with an added value in the most challenging clinical scenarios.

Feasibility and image quality of bright-blood and black-blood phase-sensitive inversion recovery (BOOST) sequence in clinical practice using for left atrial visualization in patients with atrial fibrillation

ObjectivesVisualizing left atrial anatomy including the pulmonary veins (PVs) is important for planning the procedure of pulmonary vein isolation with ablation in patients with atrial fibrillation (AF). The aims of our study are to investigate the feasibility of the 3D whole-heart bright-blood and black-blood phase-sensitive (BOOST) inversion recovery sequence in patients with AF scheduled for ablation or electro-cardioversion, and to analyze the correlation between image quality and heart rate and rhythm of patients.MethodsBOOST was performed for assessing PVs both with T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) in 45 patients with paroxysmal or permanent AF scheduled for ablation or electro-cardioversion. Image quality analyses were performed by two independent observers. Qualitative assessment was made using the Likert scale; for quantitative analysis, signal to noise ratios (SNR) and contrast to noise ratios (CNR) were calculated for each PV. Heart rate and rhythm were analyzed based on standard 12-lead ECGs.ResultsAll MTC-BOOST acquisitions achieved diagnostic quality in the PVs, while a significant proportion of T2prep-BOOST images were not suitable for assessing PVs. 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.Conclusion3D whole-heart MTC-BOOST bright-blood imaging is suitable for visualizing the PVs in patients with AF, producing diagnostic image quality in 100% of cases. However, image quality was influenced by heart rate and rhythm.Clinical relevance statementThe novel 3D whole-heart BOOST CMR sequence needs no contrast administration and is performed during free-breathing; therefore, it is easy to use for a wide range of patients and is suitable for visualizing the PVs in patients with AF.Key Points• The applicability of the novel 3D whole-heart bright-blood and black-blood phase-sensitive sequence to pulmonary vein imaging in clinical practice is unknown.• Magnetization transfer-bright-blood and black-blood phase-sensitive imaging is suitable for visualizing the pulmonary veins in patients with atrial fibrillation with excellent or good image quality.• Bright-blood and black-blood phase-sensitive cardiac magnetic resonance sequence is easy to use for a wide range of patients as it needs no contrast administration and is performed during free-breathing.

Image quality optimization: dynamic contrast-enhanced MRI of the abdomen at 3T using a continuously acquired radial golden-angle compressed sensing acquisition

IntroductionThe image quality of continuously acquired free-breathing Dynamic Contrast-Enhanced (DCE) golden-angle radial Magnetic Resonance Imaging (MRI) of abdomen suffers from motion artifacts and motion-related blurring. We propose a scheme by minimizing patients’ motion status from breathing as well as optimizing the acquiring parameters to improve image quality and diagnostic performance of DCE-MRI with Golden-Angle Radial Sparse Parallel (GRASP) sequence of abdomen.MethodsThe optimization scheme follows two principles: (1) reduce the impact on images from unpredictable and irregulate motions during examination and (2) adjust the sequence parameters to increase the number of radial views in each partition. For the assessment of image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), the severity of radial artifact, the degree of image sharpness, and a visual scoring of image quality with a 5-point scale were assessed.ResultsA total of 64 patients were included in this study before (16 men, 14 women, age: 54.9 ± 17.0) and after (18 men, 16 women, age: 58.6 ± 12.6) the optimization scheme was performed. The results showed that the SNR values of right and left lobe of liver in both plain phase and arterial phase were significantly increased (All P < 0.001) after the GRASP sequence been optimized. Significant improvements in CNR values were observed in the arterial phase (All P < 0.05). The significant differences in scores at each phase for visual scoring of image quality, noise of the right and left lobe of liver, radial artifact, and sharpness indicating that the image quality was significantly improved after the optimization (All P < 0.001).ConclusionOur study demonstrated that the optimized scheme significantly improved the image quality of liver DCE-MRI with GRASP sequence both in plain and arterial phases. The optimized scheme of GRASP sequence could be a superior alternative to conventional approach for the assessment of liver.

The value of metal artifact reduction and iterative algorithms in dual energy CT angiography in patients after complex endovascular aortic aneurysm repair

Rationale and objectivesEvaluation of the diagnostic value of linearly blended (LB) and virtual monoenergetic images (VMI) reconstruction techniques with and without metal artifacts reduction (MAR) and of adaptive statistical iterative reconstructions (ASIR) in the assessment of target vessels after branched/fenestrated endovascular aortic repair (f/brEVAR) procedures. Materials and methodsCT scans of 28 patients were used in this study. Arterial phase of examination was obtained using a dual-energy fast-kVp switching scanner. CT numbers in the aorta, celiac trunk, superior mesenteric artery, and renal arteries were measured in the following reconstructions: LB, VMI 60 keV, VMI MAR 60 keV, VMI ASIR 60 % 60 keV. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated for each reconstruction. Luminal diameters (measurements at 2 levels of stent) and subjective image quality (5-point Likert scale) were assessed (2 readers, blinded to the type of reconstruction). ResultsThe highest mean values of CNR and SNR in vascular structures were obtained in VMI MAR 60 keV (CNR 12.526 ± 2.46, SNR 17.398 ± 2.52), lower in VMI 60 keV (CNR 11.508 ± 2.01, SNR 16.524 ± 2.07) and VMI ASIR (CNR 11.086 ± 1.78, SNR 15.928 ± 1.82), and the lowest in LB (CNR 6.808 ± 0.79, SNR 11.492 ± 0.79) reconstructions. There were no statistically significant differences in the measurements of the stent width between reconstructions (p > 0.05). The highest subjective image quality was obtained in the ASIR VMI (4.25 ± 0.44) and the lowest in the MAR VMI (1.57 ± 0.5) reconstruction. ConclusionDespite obtaining the highest values of SNR and CNR in the MAR VMI reconstruction, the subjective diagnostic value was the lowest for this technique due to significant artifacts. The type of reconstruction did not significantly affect vessel diameter measurements (p > 0.05). Iterative reconstructions raised both objective and subjective image quality.

Objective detection of visual field defects with multifrequency VEPs.

To correlate multifrequency pattern reversal VEPs in quadrants (QmfrVEPs) with perimetric field losses for objective detection of visual field losses. QmfrVEP measurements were performed using four LED-based checkerboard stimulators to stimulate the four quadrants of the visual field. QmfrVEPs were measured monocularly in 5 normal subjects and in 5 glaucoma patients who showed losses in conventional Octopus perimetry. The pattern reversal frequency varied slightly between the stimulators: (11.92, 12.00, 12.08 and 12.16 reversals/sec). The responses to the different stimuli were identified by discrete Fourier analysis. VEPs were recorded using different electrode configurations, and the recording with the highest signal-to-noise ratio (SNR) was used for further analysis. QmfrVEP responses from the different quadrants can be reliably measured and separated using the 0.08 reversals/sec interstimulus reversal frequency differences. The signal-to-noise ratio in the four quadrants was significantly correlated with the equivalent visual field losses obtained with perimetry (Spearman rank correlation: P < 0.001). In the five glaucoma patients, the SNR was reduced in 15 out of the 16 quadrants with a perimetric defect, in comparison to the results in quadrants of healthy subjects. This confirms the sensitivity of the procedure. QmfrVEP responses can be measured reliably. This pilot study suggests that high SNR values exclude visual field defects and that focal defects can be identified in glaucoma patients. www. gov . NCT00494923.

Penggunaan T2 STIR dan Fat Saturation pada Pemeriksaan MRI Lumbal Kasus Hernia Nucleus Pulposus (HNP)

Background: Signal to noise ratio (SNR) is defined as the ratio of the amplitude of the signal received by the coil to the amplitude of the noise. Methods: This research was quantitative alongside an observational approach conducted at the Radiology Installation of Satya Negara Hospital, North Jakarta. Alongside a research population of Lumbar MRI patients with HNP clinical indication from October to November 2022. The research sample was ten patients aged around 25-50 years with a diagnosis of HNP. Furthermore, an MRI examination was carried out using T2 STIR and T2 Fat Saturation sequences. Hence, the results of the Lumbar MRI image were ROI performed on common areas alongside the Corpus, Discus, CSF, Spinal Cord, and HNP area. Results: This research showed there was a significant difference in SNR values in the T2 STIR and T2 Fat Saturation sequences in common areas with a p-value of 0.05. There was no significant difference in SNR values in the HNP-experienced area with a p-value of 0.05. Conclusions: After a statistical test using the Paired Sample T Test, the test results obtained were p value 0.05, namely 0.692 for the SNR value on the results of the MRI Lumbar sagittal section of the sequence T2 STIR and T2 Fat saturation in the Lumbar area experiencing HNP, which means that Ho was accepted, which means that there was no significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences in the lumbar tissue that experienced HNP. 2. The SNR value of MRI images of the lumbar sagittal section of the sequence T2 STIR and T2 Fat saturation in normal lumbar tissue including Corpus, Discus, CSF, the test results obtained are p-value 0.05. This means that Ho was rejected, which means there was a significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences. In the spinal cord area, the test results obtained were p value 0.05. This meant that Ho was accepted, which meant there was no significant difference in SNR values between the T2 STIR and T2 Fat saturation sequences.

DRF codes: Deep SNR-robust feedback codes

We present a new Deep Neural Network (DNN)-based error correction code for fading channels with output feedback, called the Deep SNR-Robust Feedback (DRF) code. At the encoder, parity symbols are generated by a Long Short Term Memory (LSTM) network based on the message, as well as the past forward channel outputs observed by the transmitter in a noisy fashion. The decoder uses a bidirectional LSTM architecture along with a Signal to Noise Ratio (SNR)-aware attention NN to decode the message. The proposed code overcomes two major shortcomings of DNN-based codes over channels with passive output feedback: (i) the SNR-aware attention mechanism at the decoder enables reliable application of the same trained NN over a wide range of SNR values; (ii) curriculum training with batch size scheduling is used to speed up and stabilize training while improving the SNR-robustness of the resulting code. We show that the DRF codes outperform the existing DNN-based codes in terms of both the SNR-robustness and the error rate in an Additive White Gaussian Noise (AWGN) channel with noisy output feedback. In fading channels with perfect phase compensation at the receiver, DRF codes learn to efficiently exploit knowledge of the instantaneous fading amplitude (which is available to the encoder through feedback) to reduce the overhead and complexity associated with channel estimation at the decoder. Finally, we show the effectiveness of DRF codes in multicast channels with feedback, where linear feedback codes are known to be strictly suboptimal. These results show the feasibility of automatic design of new channel codes using DNN-based language models.

Evaluation of the impact of magnetic field homogeneity on image quality in magnetic resonance imaging: a baseline quantitative study at 1.5 T

BackgroundMagnetic resonance images can be affected in a number of ways by magnetic field inhomogeneity. The study aimed to optimize the main magnetic field homogeneity (MFH) by assessing how magnetic field inhomogeneity affects the signal-to-noise ratio (SNR) and geometric distortion of images acquired along the diameter of a spherical volume phantom from the isocenter of the MRI scanner.ResultsThe MFH ranged between 0.10 and 0.60 ppm. The best MFH and the maximum SNR were determined in the isocenter at 400 mm field of view with the application of shim. However, for all the phantom positions, geometrical distortion in images acquired at 200 mm field of view was generally better and worse at 400 mm field of view. MFH could be optimized to reduce geometrical distortion and increase SNR by increasing the receiver bandwidth and the number of excitations whiles complementing it with shimming during image acquisition. According to Chi-square independent test, there were no significant differences (p > 0.05) in the MFH, SNR, and geometrical distortion values. Compared to findings at higher field strengths, it was observed that MRI systems of higher field strengths (greater than 1.5 T) could offer superior magnetic field homogeneity and SNR without causing observable geometrical distortion.ConclusionsThe optimal field of view for the fast field echo (FFE) sequence required to maximize MFH, SNR, and reduce distortion during image acquisition may vary across MRI systems of different field strengths. To determine the appropriate field of view, the method and results of this study could serve as a guide for medical physicists as part of their routine quality assurance test procedures.

Characterization of embroidered textile-based electrode for EMG smart wear according to stitch technique

This study fabricated and evaluated the textile-type electrodes for application to smartwear that can measure surface electromyography(sEMG). It was manufactured by lock stitch(LS) and moss stitch(MS), and the stitch distance was prepared as 1, 2, or 3 mm. The surface and compression property was measured by using the Kawabata evaluation system, and the sheet resistance and skin-electrode impedance were analyzed. The coefficient of friction(MIU) of the MS was larger than that of the LS. On the other hand, the geometrical roughness(SMD) showed a smaller value. When the same load was applied, the compressive range of the MS was larger than the LS. When it was manufactured as a leg sleeve and worn, the conductive path could be increased as the loops made of conductive yarn become flat as the loops adhere to the skin by the pressure of clothing. Accordingly, the skin-electrode impedance decreased by increasing the area in contact with the skin. As the results of the RMS(root-mean-square), the LS was higher than the MS in a stable. Nevertheless, the SNR(signal-to-noise ratio) value was lower than that of the MS because movement generated noise during operation. Therefore, more stable signal acquisition is possible when applying MS. It is expected that could be applied to producing smartwear for sEMG measurements with superior sEMG signal acquisition performance while having a softer touch and flexibility.

Ambient Light Resistant Shortwave Infrared Fluorescence Imaging for Preclinical Tumor Delineation via the pH Low-Insertion Peptide Conjugated to Indocyanine Green.

Shortwave infrared (900-1,700 nm) fluorescence imaging (SWIRFI) has shown significant advantages over visible (400-650 nm) and near-infrared (700-900 nm) fluorescence imaging (reduced autofluorescence, improved contrast, tissue resolution, and depth sensitivity). However, there is a major lag in the clinical translation of preclinical SWIRFI systems and targeted SWIRFI probes. Methods: We preclinically show that the pH low-insertion peptide conjugated to indocyanine green (pHLIP ICG), currently in clinical trials, is an excellent candidate for cancer-targeted SWIRFI. Results: pHLIP ICG SWIRFI achieved picomolar sensitivity (0.4 nM) with binary and unambiguous tumor screening and resection up to 96 h after injection in an orthotopic breast cancer mouse model. SWIRFI tumor screening and resection had ambient light resistance (possible without gating or filtering) with outstanding signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values at exposures from 10 to 0.1 ms. These SNR and CNR values were also found for the extended emission of pHLIP ICG invivo (>1,100 nm, 300 ms). Conclusion: SWIRFI sensitivity and ambient light resistance enabled continued tracer clearance tracking with unparalleled SNR and CNR values at video rates for tumor delineation (achieving a tumor-to-muscle ratio above 20). In total, we provide a direct precedent for the democratic translation of an ambient light resistant SWIRFI and pHLIP ICG ecosystem, which can instantly improve tumor resection.

Performance analysis of wireless compressed-image transmission over DST-based OFDMA systems

Multimedia data, like images, consumes significant bandwidth when transmitted over wireless systems. Therefore, compressing transmitted images becomes crucial to reduce the required bandwidth and improve energy efficiency. This work aims to analyze the performance of transmitting wireless compressed images over a recent Discrete Sine Transform (DST)-Based Orthogonal Frequency Division Multiple Access (DST-OFDMA) system. It investigates the effectiveness of several image compression methods by determining the minimum Signal-to-Noise Ratio (SNR) required for each method to achieve error-free image recovery at the receiver. This work considers different modulation schemes including 16QAM and QPSK, as well as different subcarrier mapping schemes (localized and interleaved) over vehicular A, SUI3, and uniform channels. Nine standard compression methods are used for analyzing the performance of the DST-OFDMA system and compared it with that of the conventional Discrete Fourier Transform (DFT)-based OFDMA (DFT-OFDMA) system. The results show that the performance of DST-OFDMA outperforms that of DFT-OFDMA, especially when QPSK modulation is used. Simulation results demonstrate that the interleaved DST-OFDMA (DST-IOFDMA) system, employing the SPIHT_3D compression method and QPSK modulation (over the SUI3 channel model), achieves the lowest SNR value required for compressed image recovery, approximately 18 dB. This indicates that the SPIHT_3D compression method exhibits lower power consumption compared to other methods as well as high bandwidth efficiency.

A Deep Learning Image Reconstruction Algorithm for Improving Image Quality and Hepatic Lesion Detectability in Abdominal Dual-Energy Computed Tomography: Preliminary Results

This study aimed to compare the performance of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) in improving image quality and diagnostic performance using virtual monochromatic spectral images in abdominal dual-energy computed tomography (DECT). Sixty-two patients [mean age ± standard deviation (SD): 56 years ± 13; 30 men] who underwent abdominal DECT were prospectively included in this study. The 70-keV DECT images in the portal phase were reconstructed at 5-mm and 1.25-mm slice thicknesses with 40% ASIR-V (ASIR-V40%) and at 1.25-mm slice with deep learning image reconstruction at medium (DLIR-M) and high (DLIR-H) levels and then compared. Computed tomography (CT) attenuation, SD values, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured in the liver, spleen, erector spinae, and intramuscular fat. The lesions in each reconstruction group at 1.25-mm slice thickness were counted. The image quality and diagnostic confidence were subjectively evaluated by two radiologists using a 5-point scale. For the 1.25-mm images, DLIR-M and DLIR-H had lower SD, higher SNR and CNR, and better subjective image quality compared with ASIR-V40%; DLIR-H performed the best (all P values < 0.001). Furthermore, the 1.25-mm DLIR-H images had similar SD, SNR, and CNR values as the 5-mm ASIR-V40% images (all P > 0.05). Three image groups had similar lesion detection rates, but DLIR groups exhibited higher confidence in diagnosing lesions. Compared with ASIR-V40% at 70 keV, 70-keV DECT with DLIR-H further reduced image noise and improved image quality. Additionally, it improved diagnostic confidence while ensuring a consistent lesion detection rate of liver lesions.