Title :
Medical ultrasound signal denoise based on ensemble empirical mode decomposition and nonlinear correlation information entropy
Author :
Shen Zhiyuan ; Shen Yi ; Wang Qiang
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
In practical application, medical ultrasonic signal is often polluted by trumpet type noise. The traditional band-pass filter can not be better to resolve the issue of such denoising. In this paper, we decompose medical ultrasound signal by ensemble empirical mode decomposition, and combined with the nonlinear correlation information entropy as the evaluation criteria to accomplish the removal of trumpet type noise. Through simulation experiments, we demonstrate the effectiveness of the method. Compared with wavelet threshold denoising, the proposed method is advantageous.
Keywords :
biomedical ultrasonics; correlation methods; entropy; medical signal processing; signal denoising; wavelet transforms; band-pass filter; biomedical ultrasonics; ensemble empirical mode decomposition; medical signal denoising; nonlinear correlation information entropy; trumpet type noise; wavelet threshold denoising; Additive noise; Band pass filters; Biomedical imaging; Humans; Information entropy; Medical diagnostic imaging; Noise reduction; Pollution; Signal to noise ratio; Ultrasonic imaging; Ensemble empirical mode decomposition; denoising; medical ultrasonic signal; nonlinear correlation information entropy;
Conference_Titel :
Information, Computing and Telecommunication, 2009. YC-ICT '09. IEEE Youth Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5074-9
Electronic_ISBN :
978-1-4244-5076-3
DOI :
10.1109/YCICT.2009.5382383