A Ridge Ensemble Empirical Mode Decomposition Approach to Clutter Rejection for Ultrasound Color Flow Imaging

2013 ◽  
Vol 60 (6) ◽  
pp. 1477-1487 ◽  
Author(s):  
Zhiyuan Shen ◽  
Naizhang Feng ◽  
Yi Shen ◽  
Chin-Hui Lee
Keyword(s):  
Empirical Mode Decomposition ◽  
Ensemble Empirical Mode Decomposition ◽  
Flow Imaging ◽  
Color Flow ◽  
Decomposition Approach ◽  
Clutter Rejection ◽  
Color Flow Imaging ◽  
Mode Decomposition

RIDGE REGRESSION MODEL-BASED ENSEMBLE EMPIRICAL MODE DECOMPOSITION FOR ULTRASOUND CLUTTER REJECTION

2012 ◽  
Vol 04 (01n02) ◽  
pp. 1250013
Author(s):  
ZHIYUAN SHEN ◽  
NAIZHANG FENG ◽  
YI SHEN
Keyword(s):  
Regression Model ◽  
Empirical Mode Decomposition ◽  
Ridge Regression ◽  
Ensemble Empirical Mode Decomposition ◽  
Color Flow ◽  
Clutter Rejection ◽  
Mode Decomposition ◽  
Adaptive Data Analysis ◽  
Flow Frequency ◽  
Mode Mixing

Ensemble empirical mode decomposition (EEMD) is a noise-assisted adaptive data analysis method to solve the problem of mode mixing caused by empirical mode decomposition (EMD). It is shown that the decomposition error tends to zero, as ensemble number increases to infinity in EEMD. In this paper, a novel EEMD-based ridge regression model (REEMD) is proposed, which solves the problem of mode mixing and achieves less decomposition error compared with the EEMD. When the ensemble number is small, the weights of outliers are constraint to zero to reduce the decomposition error in REEMD and the result of REEMD is asymptotic to that of EEMD, as the ensemble number increases. The proposed REEMD is suitable for tissue clutter rejection in color flow imaging system. Simulation shows that reasonable flow-frequency estimations can be achieved by REEMD and the estimation error limits to zero, as the flow frequency increases.

A novel clutter rejection scheme in color flow imaging

Ultrasonics ◽  
2006 ◽  
Vol 44 ◽  
pp. e303-e305 ◽  
Author(s):  
Pei-Dong Wang ◽  
Yi Shen ◽  
Nai-Zhang Feng
Keyword(s):  
Flow Imaging ◽  
Color Flow ◽  
Clutter Rejection ◽  
Color Flow Imaging

Applications of variational mode decomposition in seismic time-frequency analysis

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. V365-V378 ◽  
Author(s):  
Wei Liu ◽  
Siyuan Cao ◽  
Yangkang Chen
Keyword(s):  
Empirical Mode Decomposition ◽  
Frequency Analysis ◽  
Synthetic Data ◽  
Ensemble Empirical Mode Decomposition ◽  
Variational Mode Decomposition ◽  
Intrinsic Mode Functions ◽  
Decomposition Approach ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Mode Decomposition

We have introduced a novel time-frequency decomposition approach for analyzing seismic data. This method is inspired by the newly developed variational mode decomposition (VMD). The principle of VMD is to look for an ensemble of modes with their respective center frequencies, such that the modes collectively reproduce the input signal and each mode is smooth after demodulation into baseband. The advantage of VMD is that there is no residual noise in the modes and it can further decrease redundant modes compared with the complete ensemble empirical mode decomposition (CEEMD) and improved CEEMD (ICEEMD). Moreover, VMD is an adaptive signal decomposition technique, which can nonrecursively decompose a multicomponent signal into several quasi-orthogonal intrinsic mode functions. This new tool, in contrast to empirical mode decomposition (EMD) and its variations, such as EEMD, CEEMD, and ICEEMD, is based on a solid mathematical foundation and can obtain a time-frequency representation that is less sensitive to noise. Two tests on synthetic data showed the effectiveness of our VMD-based time-frequency analysis method. Application on field data showed the potential of the proposed approach in highlighting geologic characteristics and stratigraphic information effectively. All the performances of the VMD-based approach were compared with those from the CEEMD- and ICEEMD-based approaches.

Real-time adaptive clutter rejection filtering in color flow imaging using power method iterations

2006 ◽  
Vol 53 (9) ◽  
pp. 1597-1608 ◽  
Author(s):  
L. Lovstakken ◽  
S. Bjaerum ◽  
K. Kristoffersen ◽  
R. Haaverstad ◽  
H. Torp
Keyword(s):  
Real Time ◽  
Flow Imaging ◽  
Power Method ◽  
Color Flow ◽  
Clutter Rejection ◽  
Color Flow Imaging

An Advanced Filter Adaptive to Non-Stationary Clutter in Ultrasonic Color Flow Imaging

2011 ◽  
Vol 186 ◽  
pp. 141-145
Author(s):  
Cong Sheng Xie ◽  
Dong C. Liu
Keyword(s):  
Blood Flow ◽  
Adaptive Filter ◽  
Constant Velocity ◽  
Cutoff Frequency ◽  
Flow Imaging ◽  
Color Flow ◽  
Flow Estimation ◽  
Clutter Rejection ◽  
Color Flow Imaging ◽  
Tissue Motion

Traditional clutter rejection methods are based on the hypothesis that the clutter signal originates from stationary or moving tissue with a constant velocity, and they are not valid when there exists considerable acceleration of tissue motion. In this paper, we propose an advanced clutter filter adapted to accelerated tissue motion. It uses the instantaneous frequency to realize the DC remove, and uses the bandwidth of the clutter signal to choose the cutoff frequency of the wall filter, Simulation shows this advanced adaptive filter can efficiently attenuate the non-stationary clutter signals and improves the accuracy and the flexibility of the blood flow estimation.

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