scholarly journals Comparison between STIR and T2-weighted SPAIR sequences in the evaluation of inflammatory sacroiliitis: diagnostic performance and signal-to-noise ratio

2020 ◽  
Vol 53 (4) ◽  
pp. 223-228
Author(s):  
Vitor Faeda Dalto ◽  
Rodrigo Luppino Assad ◽  
Mario Müller Lorenzato ◽  
Michel Daoud Crema ◽  
Paulo Louzada-Junior ◽  
...  
Keyword(s):  
Diagnostic Performance ◽  
Recent Literature ◽  
Signal To Noise Ratio ◽  
Sacroiliac Joints ◽  
Signal To Noise ◽  
Asas Criteria ◽  
The Mean ◽  
Noise Ratio ◽  
Magnetic Resonance Imaging Mri ◽  
Active Inflammation

Abstract Objective: To compare two different fat-saturated magnetic resonance imaging (MRI) techniques-STIR and T2 SPAIR-in terms of image quality, as well as in terms of their diagnostic performance in detecting sacroiliac joints (SIJ) active inflammation. Materials and Methods: We included 69 consecutive patients with suspected spondyloarthritis undergoing MRI between 2012 and 2014. The signal-to-noise ratio (SNR) was calculated with the method recommended by the American College of Radiology. Two readers evaluated SIJ MRI following ASAS criteria to assess diagnostic performance regarding the detection of active SIJ inflammation. T1 SPIR Gd+ sequence was used as the reference standard. Results: The mean SNR was 72.8 for the T1 SPIR Gd+ sequence, compared with 14.1 and 37.6 for the STIR and T2 SPAIR sequences, respectively. The sensitivity and specificity of STIR and SPAIR T2 sequences did not show any statistically significant differences, for the diagnosis of sacroiliitis with active inflammation. Conclusion: Our results corroborate those in the recent literature suggesting that STIR sequences are not superior to T2 SPAIR sequences for SIJ evaluation in patients with suspected spondyloarthritis. On 1.5-T MRI, T2-weighted SPAIR sequences provide better SNRs than do STIR sequences, which reinforces that T2 SPAIR sequences may be an advantageous option for the evaluation of sacroiliitis.

Clinical impact of ultra-high b-value (3000 s/mm2) diffusion-weighted magnetic resonance imaging in prostate cancer at 3T: comparison with b-value of 2000 s/mm2

2021 ◽  
pp. 20210465
Author(s):  
Tsutomu Tamada ◽  
Ayumu Kido ◽  
Yu Ueda ◽  
Mitsuru Takeuchi ◽  
Takeshi Fukunaga ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diagnostic Performance ◽  
Signal To Noise Ratio ◽  
B Value ◽  
Single Shot ◽  
Signal To Noise ◽  
High B Value ◽  
Diffusion Weighted ◽  
Significant Difference ◽  
Noise Ratio

Objective: High b-value diffusion-weighted imaging (hDWI) with a b-value of 2000 s/mm2 provides insufficient image contrast between benign and malignant tissues and an overlap of apparent diffusion coefficient (ADC) between Gleason grades (GG) in prostate cancer (PC). We compared image quality, PC detectability, and discrimination ability for PC aggressiveness between ultra-high b-value DWI (uhDWI) of 3000 s/mm2 and hDWI. Methods: The subjects were 49 patients with PC who underwent 3T multiparametric MRI. Single-shot echo-planar DWI was acquired with b-values of 0, 2000, and 3000 s/mm2. Anatomical distortion of prostate (AD), signal intensity of benign prostate (PSI), and lesion conspicuity score (LCS) were assessed using a 4-point scale; and signal-to-noise ratio, contrast-to-noise ratio, and mean ADC (×10–3 mm2/s) of lesion (lADC) and surrounding benign region (bADC) were measured. Results: PSI was significantly lower in uhDWI than in hDWI (p < 0.001). AD, LCS, signal-to-noise ratio, and contrast-to-noise ratio were comparable between uhDWI and hDWI (all p > 0.05). In contrast, lADC was significantly lower than bADC in both uhDWI and hDWI (both p < 0.001). In comparison of lADC between tumors of ≤GG2 and those of ≥GG3, both uhDWI and hDWI showed significant difference (p = 0.007 and p = 0.021, respectively). AUC for separating tumors of ≤GG2 from those of ≥GG3 was 0.731 in hDWI and 0.699 in uhDWI (p = 0.161). Conclusion: uhDWI suppressed background signal better than hDWI, but did not contribute to increased diagnostic performance in PC. Advances in knowledge: Compared with hDWI, uhDWI could not contribute to increased diagnostic performance in PC.

Power spectral analysis of the diaphragm electromyogram

1983 ◽  
Vol 54 (6) ◽  
pp. 1579-1584 ◽  
Author(s):  
T. K. Aldrich ◽  
J. M. Adams ◽  
N. S. Arora ◽  
D. F. Rochester
Keyword(s):  
Power Spectrum ◽  
Signal To Noise Ratio ◽  
Normal Subjects ◽  
Chronic Obstructive ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Mean Values ◽  
The Mean ◽  
Noise Ratio ◽  
Diaphragm Fatigue

We studied the power spectrum of the diaphragm electromyogram (EMG) at frequencies between 31 and 246 Hz in four young normal subjects and five patients with chronic obstructive lung disease (COPD). Diaphragm EMGs were analyzed during spontaneous breathing and maximum inspiratory efforts to determine the effect of signal-to-noise ratio on the power spectrum and if treadmill exercise to dyspnea was associated with diaphragm fatigue. We found that the centroid frequencies of the power spectra (fc) were strongly correlated (r = 0.93) with ratios of power at high frequencies to power at low frequencies (H/L) for all subjects. Of the two indices, H/L had the largest standard deviation expressed as a percentage of the mean. The mean values of both of these decreased significantly after exercise, fc from 100.2 to 97.3 and H/L from 1.07 to 0.97. Signal-to-noise ratios were higher in maximal inspiratory efforts and after exercise in normal subjects and higher in COPD patients. The signal-to-noise ratio was correlated negatively with fc and H/L, indicating that these indices of the shape of the power spectrum are influenced by signal strength and noise levels as well as muscle function. We conclude that the fc and H/L index similar qualities of the power spectrum, that they are partially determined by the signal-to-noise ratio, and that, in some cases, exercise to dyspnea is associated with apparently mild diaphragm fatigue.

SIGNAL‐TO‐NOISE RATIO AND RECORD QUALITY

Geophysics ◽  
1964 ◽  
Vol 29 (6) ◽  
pp. 922-925 ◽  
Author(s):  
Arne Junger
Keyword(s):  
Phase Shift ◽  
Signal To Noise Ratio ◽  
Random Phase ◽  
Large Change ◽  
Seismic Record ◽  
Signal To Noise ◽  
Change In The Mean ◽  
The Mean ◽  
Noise Ratio

The appearance of a seismic record is a function of the signal‐to‐noise ratio. This ratio is expressed quantitatively, but it can not be measured on the record. The quality of the record is expressed by the lineup of events and constancy of character across the record, but is generally not expressed numerically. The appearance of the record is here expressed numerically by the mean phase shift from perfect lineup of various events. A statistical relationship is established between this mean phase shift and the signal‐to‐noise ratio. A seismic record may be approximated by considering the signal to have a sinusoidal waveform and the noise to be a continuous sine wave with the same frequency as the signal and with random phase shift with respect to the signal on various traces. The resulting record will show a random phase shift, the mean value of which is a function of the signal‐to‐noise ratio. A plot of these two values shows that with increasing signal‐to‐noise ratio there is very little change in the mean phase shift, and thus of the quality of the record, until a value of one‐half for the signal‐to‐noise ratio is reached, showing that the noise dominates the record up to this point. For values of the signal‐to‐noise ratio between one‐half and two, there is a large change in the mean phase shift, indicating a strong visual improvement for this range. For a signal‐to‐noise ratio larger than two, the signal predominates visually, and only a slight improvement in quality can be obtained with additional improvements in the signal‐to‐noise ratio. These conclusions are in agreement with experimental data published elsewhere.

An MMSE Overlay Cognitive Wireless System

2013 ◽  
Vol 5 (1) ◽  
pp. 1-13
Author(s):  
Monirosharieh Vameghestahbanati ◽  
Hasan S. Mir ◽  
Mohamed El-Tarhuni
Keyword(s):  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Wireless System ◽  
Transmitter Power ◽  
Channel Estimate ◽  
Squared Error ◽  
The Mean ◽  
Noise Ratio ◽  
New System

In this paper, the authors propose a framework that allows an overlay (new) system to operate simultaneously with a legacy (existing) system. By jointly optimizing the transmitter and the receiver filters of the overlay system, the sum of the mean-squared error (MSE) of the new system plus the excess MSE in the existing system due to the introduction of the overlay system is minimized. The effects of varying key parameters such as the overlay transmitter power and the amount of overlap between the legacy and the overlay systems are investigated. Furthermore, the sensitivity of the system to accuracy of signal-to-noise ratio (SNR) estimate and the channel estimate is also examined.

scholarly journals Comparison of conventional and Si-photomultiplier-based PET systems for image quality and diagnostic performance

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jenny Oddstig ◽  
Sigrid Leide Svegborn ◽  
Helen Almquist ◽  
Ulrika Bitzén ◽  
Sabine Garpered ◽  
...  
Keyword(s):  
Image Quality ◽  
Diagnostic Performance ◽  
Signal To Noise Ratio ◽  
Tnm Classification ◽  
Activity Level ◽  
Reconstruction Algorithms ◽  
Signal To Noise ◽  
Standardized Uptake Values ◽  
Pet Ct ◽  
Noise Ratio

Abstract Background A new generation of positron emission tomography with computed tomography (PET-CT) was recently introduced using silicon (Si) photomultiplier (PM)-based technology. Our aim was to compare the image quality and diagnostic performance of a SiPM-based PET-CT (Discovery MI; GE Healthcare, Milwaukee, WI, USA) with a time-of-flight PET-CT scanner with a conventional PM detector (Gemini TF; Philips Healthcare, Cleveland, OH, USA), including reconstruction algorithms per vendor’s recommendations. Methods Imaging of the National Electrical Manufacturers Association IEC body phantom and 16 patients was carried out using 1.5 min/bed for the Discovery MI PET-CT and 2 min/bed for the Gemini TF PET-CT. Images were analysed for recovery coefficients for the phantom, signal-to-noise ratio in the liver, standardized uptake values (SUV) in lesions, number of lesions and metabolic TNM classifications in patients. Results In phantom, the correct (> 90%) activity level was measured for spheres ≥17 mm for Discovery MI, whereas the Gemini TF reached a correct measured activity level for the 37-mm sphere. In patient studies, metabolic TNM classification was worse using images obtained from the Discovery MI compared those obtained from the Gemini TF in 4 of 15 patients. A trend toward more malignant, inflammatory and unclear lesions was found using images acquired with the Discovery MI compared with the Gemini TF, but this was not statistically significant. Lesion-to-blood-pool SUV ratios were significantly higher in images from the Discovery MI compared with the Gemini TF for lesions smaller than 1 cm (p < 0.001), but this was not the case for larger lesions (p = 0.053). The signal-to-noise ratio in the liver was similar between platforms (p = 0.52). Also, shorter acquisition times were possible using the Discovery MI, with preserved signal-to-noise ratio in the liver. Conclusions Image quality was better with Discovery MI compared to conventional Gemini TF. Although no gold standard was available, the results indicate that the new PET-CT generation will provide potentially better diagnostic performance.

scholarly journals An Image Filter Based on Multiobjective Genetic Algorithm and Shearlet Transformation

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhi-yong Fan ◽  
Quan-sen Sun ◽  
Ze-xuan Ji ◽  
Kai Hu
Keyword(s):  
Genetic Algorithm ◽  
Wavelet Decomposition ◽  
Signal To Noise Ratio ◽  
Target Function ◽  
Threshold Value ◽  
Rician Noise ◽  
Signal To Noise ◽  
Multiobjective Genetic Algorithm ◽  
Noise Ratio ◽  
Magnetic Resonance Imaging Mri

Rician noise pollutes magnetic resonance imaging (MRI) data, making data’s postprocessing difficult. In order to remove this noise and avoid loss of details as much as possible, we proposed a filter algorithm using both multiobjective genetic algorithm (MOGA) and Shearlet transformation. Firstly, the multiscale wavelet decomposition is applied to the target image. Secondly, the MOGA target function is constructed by evaluation methods, such as signal-to-noise ratio (SNR) and mean square error (MSE). Thirdly, MOGA is used with optimal coefficients of Shearlet wavelet threshold value in a different scale and a different orientation. Finally, the noise-free image could be obtained through inverse wavelet transform. At the end of the paper, experimental results show that this proposed algorithm eliminates Rician noise more effectively and yields better peak signal-to-noise ratio (PSNR) gains compared with other traditional filters.

A wavelet-based method for MRI liver image denoising

2019 ◽  
Vol 64 (6) ◽  
pp. 699-709 ◽  
Author(s):  
Mohammed Nabih Ali
Keyword(s):  
Image Denoising ◽  
Wavelet Transforms ◽  
Signal To Noise Ratio ◽  
Optimal Parameters ◽  
Signal To Noise ◽  
Family Level ◽  
Noise Ratio ◽  
Magnetic Resonance Imaging Mri ◽  
Liver Image ◽  
Wavelet Family

Abstract Image denoising stays be a standout amongst the primary issues in the field of image processing. Several image denoising algorithms utilizing wavelet transforms have been presented. This paper deals with the use of wavelet transform for magnetic resonance imaging (MRI) liver image denoising using selected wavelet families and thresholding methods with appropriate decomposition levels. Denoised MRI liver images are compared with the original images to conclude the most suitable parameters (wavelet family, level of decomposition and thresholding type) for the denoising process. The performance of our algorithm is evaluated using the signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR) and mean square error (MSE). The results show that the Daubechies wavelet family of the tenth order with first and second of the levels of decomposition are the most optimal parameters for MRI liver image denoising.

scholarly journals Interleaved Acoustic Environments: Impact of an Auditory Scene Classification Procedure on Speech Perception in Cochlear Implant Users

2021 ◽  
Vol 25 ◽  
pp. 233121652110141
Author(s):  
Anja Eichenauer ◽  
Uwe Baumann ◽  
Timo Stöver ◽  
Tobias Weissgerber
Keyword(s):  
Speech Perception ◽  
Cochlear Implant ◽  
Signal To Noise Ratio ◽  
Scene Classification ◽  
Signal To Noise ◽  
Acoustic Environment ◽  
The Mean ◽  
Noise Ratio ◽  
Acoustic Environments ◽  
The Impact

Clinical speech perception tests with simple presentation conditions often overestimate the impact of signal preprocessing on speech perception in complex listening environments. A new procedure was developed to assess speech perception in interleaved acoustic environments of different complexity that allows investigation of the impact of an automatic scene classification (ASC) algorithm on speech perception. The procedure was applied in cohorts of normal hearing (NH) controls and uni- and bilateral cochlear implant (CI) users. Speech reception thresholds (SRTs) were measured by means of a matrix sentence test in five acoustic environments that included different noise conditions (amplitude modulated and continuous), two spatial configurations, and reverberation. The acoustic environments were encapsulated in a randomized, mixed order single experimental run. Acoustic room simulation was played back with a loudspeaker auralization setup with 128 loudspeakers. 18 NH, 16 unilateral, and 16 bilateral CI users participated. SRTs were evaluated for each individual acoustic environment and as mean-SRT. Mean-SRTs improved by 2.4 dB signal-to-noise ratio for unilateral and 1.3 dB signal-to-noise ratio for bilateral CI users with activated ASC. Without ASC, the mean-SRT of bilateral CI users was 3.7 dB better than the SRT of unilateral CI users. The mean-SRT indicated significant differences, with NH group performing best and unilateral CI users performing worse with a difference of up to 13 dB compared to NH. The proposed speech test procedure successfully demonstrated that speech perception and benefit with ASC depend on the acoustic environment.

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