NDLI: A new adaptive denoising method based on empirical mode decomposition in ultrasonic elastography

Content Provider	IEEE Xplore Digital Library
Author	Guang Qiu Jieping Liu Tao Ling Hairong Zheng
Copyright Year	2011
Description	Author affiliation: Paul C.Lauterbur Research Center For Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, China (Tao Ling; Hairong Zheng) \|\| School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China (Guang Qiu; Jieping Liu)
Abstract	Important soft tissue parameters such as elasticity can be obtained by ultrasonic elastic imaging. Nonetheless, the radio frequency (RF) data received by ultrasonic transducer are always mixed up with noises. In this paper, we develop a new adaptive signal processing method for ultrasonic elastography. The key part of the method is the empirical mode decomposition (EMD) which a method associated with the Hilbert-Huang transform (HHT). EMD method is well suited to analyzing non-stationary and non-linear signal such as biomedical signal. The raw RF data is firstly decomposed into several intrinsic mode functions (IMF) using EMD. Then we analyze its energy distribution and set a to control the signal reconstruction. In the experimental study, the data gathered both from tissue mimicking phantom and volunteer are tested. The results obtained with the new method are in good agreement with those obtained with the conventional one, the interferences are removed effectively especially in the low frequency domain.
Starting Page	68
Ending Page	72
File Size	1075753
Page Count	5
File Format	PDF
ISBN	9781612847719
e-ISBN	9781612847740
DOI	10.1109/ICMT.2011.6001652
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Ultrasonic imaging Empirical mode decomposition Radio frequency data Noise Phantoms Transforms Elasticity Acoustics Elastography
Content Type	Text
Resource Type	Article

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