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Wen Liu
Sichuan University

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Speckle Reduction of Ultrasound Elastography with Bilateral Filter Xiaoming Zhou; Wen Liu; Dong C. Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 4: April 2013
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Ultrasound elastography has been well applied in early tumor diagnosis for obtaining tissue stiffness information. Elastograpyy may provide useful clinical information for the tissue characterization. But ultrasonic wave interference will produce speckle in both phase and envelope. So in conventional ultrasound elastography, there are noise artifacts which produce some misdiagnosis. In this paper, we investigate bilateral filter de-noising method to reduce the speckle. Because the bilateral filter de-noising method can greatly smooth the speckle at the same time protect the lesion edge well, it has been well proved good impact in B-mode. But in ultrasound elastography, the bilateral filter hasn’t been used. So we use the bilateral filter to reduce artifacts to prove the performance of this method .In the experiment, because of the bilateral filter de-noising method, the noise artifacts will be reduced largely. We use SNRe and CNRe to verify the performance of the bilateral filter and finally this method proved a significant improvement to SNRe and CNRe. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2343
Tissue Flow Detection Using Fuzzy Logic Method in Color Flow Imaging Xiaoming Zhou; Wen Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i9.pp6840-6845

Abstract

Tissue/flow detection is critical for high quality 2-D color flow image. The traditional tissue/flow detection method is based on one or several thresholds which are used for parameters after autocorrelation. Generally a lot of parameters: flow magnitude, variance and velocity are applied for tissue/flow detection. But this method may not distinguish tissue/flow because of moving tissue or noise. So in this paper, fuzzy logic method with multi-level range based on in vivo carotid I/Q data was proposed with three parameters: echo amplitude, flow magnitude and Flow variance for tissue/flow detection and then decision look-up-table (LUT) was designed for real time display. Experiment results shows that fuzzy logic method was improved for tissue flow detection significantly and can get high quality 2-D color flow image.
Co-Authors Dong C. Liu Xiaoming Zhou