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1.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 32(6): 1179-84, 2015 Dec.
Article in Chinese | MEDLINE | ID: mdl-27079083

ABSTRACT

Electrocardiogram (ECG) signals are susceptible to be disturbed by 50 Hz power line interference (PLI) in the process of acquisition and conversion. This paper, therefore, proposes a novel PLI removal algorithm based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD). Firstly, according to the morphological differences in ECG waveform characteristics, the noisy ECG signal was decomposed into the mutated component, the smooth component and the residual component by MCA. Secondly, intrinsic mode functions (IMF) of PLI was filtered. The noise suppression rate (NSR) and the signal distortion ratio (SDR) were used to evaluate the effect of de-noising algorithm. Finally, the ECG signals were re-constructed. Based on the experimental comparison, it was concluded that the proposed algorithm had better filtering functions than the improved Levkov algorithm, because it could not only effectively filter the PLI, but also have smaller SDR value.


Subject(s)
Algorithms , Electrocardiography , Humans
2.
Magn Reson Imaging ; 25(10): 1409-16, 2007 Dec.
Article in English | MEDLINE | ID: mdl-17566688

ABSTRACT

Diffusion weighting in MRI is commonly achieved with the pulsed-gradient spin-echo (PGSE) method. When combined with spin-warping image formation, this method often results in ghosts due to the sample's macroscopic motion. It has been shown experimentally (Kennedy and Zhong, MRM 2004;52:1-6) that these motion artifacts can be effectively eliminated by the distant dipolar field (DDF) method, which relies on the refocusing of spatially modulated transverse magnetization by the DDF within the sample itself. In this report, diffusion-weighted images (DWIs) using both DDF and PGSE methods in the presence of macroscopic sample motion were simulated. Numerical simulation results quantify the dependence of signals in DWI on several key motion parameters and demonstrate that the DDF DWIs are much less sensitive to macroscopic sample motion than the traditional PGSE DWIs. The results also show that the dipolar correlation distance (d(c)) can alter contrast in DDF DWIs. The simulated results are in good agreement with the experimental results reported previously.


Subject(s)
Algorithms , Artifacts , Diffusion Magnetic Resonance Imaging/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Models, Neurological , Movement , Computer Simulation , Humans , Reproducibility of Results , Sensitivity and Specificity
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