Improvement of tomographic reconstruction in bone SPECT

Summary Aim: The comparison between iterative reconstruction and filtered backprojection in the reconstruction of bone SPECT in the diagnosis of skeletal metastases. Patients, methods: 47 consecutive patients (vertebral segments: n = 435), with suspected malignancy of the vertebral column, were examined by bone scintigraphy and MRI (maximal interval between the two procedures ± 5 weeks). The SPECT-data were reconstructed with an iterative algorithm (ISA) and with filtered backprojection. We defined semiquantitative criteria in order to assess the quality of the tomograms. Conventional reconstruction was performed both by a Wiener-filter and a low-pass-filter. Iterative reconstruction was performed by the ISA algorithm. The clinical evaluation of the different reconstruction algorithms was performed by MRI as the gold-standard. Results: Sensitivity (%): 87.3 (ISA), 86.4 (low-pass), 79.7 (Wiener); specificity (%): 95.3 (ISA), 95 (low-pass), 85.4 (Wiener). The sensitivity of iterative reconstructed SPECT and low-pass reconstructed SPECT was significantly higher (p <0.05) compared with the sensitivity of SPECT reconstructed by the Wiener-filter. The specificity of iterative reconstruction ISA and low-pass-filter reconstructed SPECT were significantly higher compared with the SPECT data reconstructed by the Wiener-filter. ISA was significantly superior to the Wiener- SPECT relating to all criteria of quality. Iterative reconstruction was significantly superior to the low-pass-SPECT relating to 2 of 3 criteria. In addition the Wiener-SPECT was significantly inferior to the low-pass-SPECT regarding to 2 of 3 criteria. Conclusion: In our series the iterative algorithm ISA was the method of choice in the reconstruction of bone SPECT data. In comparison with conventional algorithms ISA offers a significantly higher quality of the tomograms and yields a high diagnostic accuracy.

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A Novel Image Restoration Method based on Iterative Algorithm

International Journal of Circuits, Systems and Signal Processing ◽

10.46300/9106.2021.15.57 ◽

2021 ◽

Vol 15 ◽

pp. 519-524

Author(s):

Saiyan Wu ◽

Hui Yang

Keyword(s):

Iterative Algorithm ◽

Blind Deconvolution ◽

Convergence Result ◽

The Other ◽

Pass Filter ◽

Low Pass Filter ◽

Blind Image Deblurring ◽

Low Pass ◽

Blind Restoration ◽

Restoration Method

In the paper, we proposed a new iterative algorithm and use a entirely new iterative factor. Firstly, we adopt the Exp function in the iterative factor, because we want each iterative result preserves the nonnegative constraint; Secondly, we make the iterative factor in a reciprocal form ,this way can produce two advantages, one is we can get a more stable and continuous results after each iteration; the other is we can achieve this algorithm in hardware more convenient. Thirdly, we add a low-pass filter and the edge of the scale in the iterative factor, this way we can get a better result, the image SNR is higher and the MSE is lower. Meanwhile for the image sequence, we adopt the two-step iterative algorithm. The result shows the algorithm own the faster convergence speed and the better convergence result. Different from the other algorithm for blind restoration, although we should select the parameter in the starting of the algorithm, the algorithm doesn’t sensitive for the parameter. So the algorithm possesses very strong adaptability for the blind image deblurring. So a novel algorithm based on an iterative and nonnegative algorithm was proposed to perform blind deconvolution.

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A Multistage Algorithm Design for Electrocardiogram Signal Denoising

Journal of Circuits System and Computers ◽

10.1142/s0218126621500614 ◽

2020 ◽

pp. 2150061

Author(s):

Amel Harkat ◽

Redha Benzid ◽

Noureddine Athamena

Keyword(s):

Algorithm Design ◽

Wiener Filter ◽

Experimental Tests ◽

Pass Filter ◽

Low Pass Filter ◽

Ecg Signals ◽

Low Pass ◽

Quantitative Results ◽

Restoration Ability ◽

Surrounding Areas

This work describes a new scheme for denoising noisy electrocardiogram (ECG) signals. In the first step, the noise variance is estimated using the well-known DONOHO’s estimator followed by the wavelet-based baseline wander removing. In the second step, the estimated variance is employed in the adaptive 1D Wiener filter to reduce the additive noise. Next, a Low Pass filter, based on the FFT, is applied on the resulting denoised signal. Furthermore, a cascaded Savitzky–Golay (SG) smoother filter is applied to refine the restoration process. The final step consists in the recovering of the [Formula: see text]-peaks and the surrounding areas. It can be reported that the suggested algorithm is optimal for the additive Gaussian noise and is useful for other types of noises. Both qualitative and quantitative results, achieved from several experimental tests, establish high-quality restoration ability and the efficiency of the proposed method. Thus, when compared to some powerful techniques recently published, the designed algorithm demonstrates very competitive performances.

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Evaluation of Bus Vibration Comfort Based on Passenger Crowdsourcing Mode

Mathematical Problems in Engineering ◽

10.1155/2016/2132454 ◽

2016 ◽

Vol 2016 ◽

pp. 1-10 ◽

Cited By ~ 3

Author(s):

Hong Zhao ◽

Li-Lu Guo ◽

Xiang-Yan Zeng

Keyword(s):

Evaluation System ◽

Experimental System ◽

Pass Filter ◽

Low Pass Filter ◽

Vibration Signals ◽

Vibration Data ◽

Low Pass ◽

Space Coordinate ◽

Iso 2631

Vibration comfort is an important factor affecting the quality of service (QoS) of bus. In order to make people involved in supervising bus’s vibration comfort and improve passengers’ riding experience, a novel mode of passenger crowdsourcing is introduced. In this paper, comfort degree of bus vibration is calculated from bus’s vibration signals collected by passengers’ smartphones and sent through WiFi to the Boa web server which shows the vibration comfort on the LCD deployed in bus and maybe trigger alarm lamp when the vibration is beyond the threshold. Three challenges here have been overcome: firstly, space coordinate transformation algorithm is used to solve the constant drift of signals collected; secondly, a low-pass filter is designed to isolate gravity from signals real-timely via limited computing resources; thirdly, an embedded evaluation system is developed according to the calculation procedure specified by criterion ISO 2631-1997. Meanwhile, the model proposed is tested in a practical running environment, the vibration data in whole travel are recorded and analyzed offline. The results show that comfort degree of vibration obtained from the experimental system is identical with the truth, and this mode is proved to be effective.

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MTF Compensation Combining Reciprocal Cell with Shift Invariance Wavelet

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.48-49.719 ◽

2011 ◽

Vol 48-49 ◽

pp. 719-723

Author(s):

Zhao Jun Liu ◽

Zhi Zhang ◽

De Shen Xia

Keyword(s):

Cutoff Frequency ◽

Band Pass Filter ◽

Test Results ◽

Pass Filter ◽

Low Pass Filter ◽

Low Pass ◽

Shift Invariance ◽

Band Pass ◽

Better Than

On remote sensing imaging platform, quality of image is normally degraded by aliasing. The low-pass filter is commonly used to dealiasing. However low-pass filter introduces error for frequencies above its cutoff frequency. And the removed aliasing is also valuable information. To retain the valuable information, we propose a restoration based on band-pass filter. Firstly, the image is transformed into frequency domain. A restoration of reciprocal cell is adopted. It is based on geometrical characteristics of sensors. As a result, the superposition parts are separated from spectrum inside the bandwidth. Then aliasing spectrum is put into right position. Inverse filter is used to deblurring and remove the color noise. Finally, the shift invariance wavelet is combined to reduce the white noise. The test results indicate that the proposed restoration is better than conventional restorations. Valuable information of the restored spectrum is more than degraded spectrum. So this proposed method will be beneficial in the field of practical projects.

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CONVERGENCE OF A CONVOLUTION-FILTERING-BASED ALGORITHM FOR EMPIRICAL MODE DECOMPOSITION

Advances in Adaptive Data Analysis ◽

10.1142/s1793536909000205 ◽

2009 ◽

Vol 01 (04) ◽

pp. 561-571 ◽

Cited By ~ 11

Author(s):

CHAO HUANG ◽

LIHUA YANG ◽

YANG WANG

Keyword(s):

Empirical Mode Decomposition ◽

Iterative Algorithm ◽

Moving Average ◽

Limit Function ◽

Continuous Variables ◽

Pass Filter ◽

Low Pass Filter ◽

Mode Decomposition ◽

Low Pass ◽

Convolution Filters

Lin et al. propose the iterative Toeplitz filters algorithm as an alternative iterative algorithm for Empirical Mode Decomposition (EMD). In this alternative algorithm, the average of the upper and lower envelopes is replaced by certain "moving average" obtained through a low-pass filter. Performing the traditional sifting algorithm with such moving averages is equivalent to iterating certain convolution filters (finite length Toeplitz filters). This paper studies the convergence of this algorithm for signals of continuous variables, and proves that the limit function of this iterative algorithm is an ideal high-pass filtering process.

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Analysis and Suppression of High-Frequency Harmonics of High Power Photovoltaic Inverter System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.556-562.1573 ◽

2014 ◽

Vol 556-562 ◽

pp. 1573-1576

Author(s):

Pei Deng ◽

You Xin Yuan ◽

Liang Yuan ◽

Ping Kuang ◽

Jing Chen

Keyword(s):

High Power ◽

High Frequency ◽

Electric Energy ◽

Photovoltaic System ◽

Pass Filter ◽

Low Pass Filter ◽

Result Show ◽

Low Pass ◽

Energy Grid

According to the growing need for renewable energy. Grid-connected photovoltaic system is used in many territories. To suppress the high-frequency harmonics of high power photovoltaic inverter, a LC low pass filter (LPF) has been proposed in this paper. The following have been done in the study: analysis of the high power photovoltaic inverter system and its harmonics, method of high-frequency harmonics suppression, and simulation of high-frequency harmonics suppression. According to the normalization method, the parameters of LPF are calculated. Then the parameters are put into a simulation model. The simulation result show that THD is 7.26%. It is much less than the former 78.19%. So it can be widely used in power system to suppress the high-frequency and to ensure the quality of electric energy.

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Toward Improvement of Resistance Testing Reliability

Journal of Engineering and Technological Sciences ◽

10.5614/j.eng.technol.sci.2021.53.2.1 ◽

2021 ◽

Vol 53 (2) ◽

pp. 210201

Author(s):

I. K.A.P. Utama ◽

Dian Purnamasari ◽

I Ketut Suastika ◽

Nurhadi Nurhadi ◽

Giles Thomas

Keyword(s):

Test Performance ◽

Resistance Testing ◽

Pass Filter ◽

Low Pass Filter ◽

Testing Procedures ◽

Benchmark Tests ◽

Low Pass ◽

Resistance Data ◽

Track Test

. Periodically conducting a benchmark test with estimated uncertainty is important to improve the quality of resistance predictions and understand the influence of instrumentation, testing procedures and analysis techniques. The LHI-007 Ro-Ro Ferry ship model, made available by the Maritime Research Institute Netherlands (MARIN), was used for benchmark testing from 2010 to 2018 at the Indonesian Hydrodynamic Laboratory. Comparisons were made between filtering the resistance data with a low-pass filter and with a Kalman filter. This work shows how benchmark tests can be used to track test performance over a longer period and proposes techniques to improve the uncertainty in the resistance results.

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