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全方向M型心動圖運動曲線檢測算法的應(yīng)用研究

王琨,  黃立勤,  鄭鑫

王琨, 黃立勤, 鄭鑫. 全方向M型心動圖運動曲線檢測算法的應(yīng)用研究[J]. 電子與信息學(xué)報, 2016, 38(7): 1660-1665. doi: 10.11999/JEIT151089
引用本文: 王琨, 黃立勤, 鄭鑫. 全方向M型心動圖運動曲線檢測算法的應(yīng)用研究[J]. 電子與信息學(xué)報, 2016, 38(7): 1660-1665. doi: 10.11999/JEIT151089
WANG Kun, HUANG Liqin, ZHENG Xin. Application of Motion Curve Edge Detection Algorithm in Omni-directional M-mode Echocardiography[J]. Journal of Electronics & Information Technology, 2016, 38(7): 1660-1665. doi: 10.11999/JEIT151089
Citation: WANG Kun, HUANG Liqin, ZHENG Xin. Application of Motion Curve Edge Detection Algorithm in Omni-directional M-mode Echocardiography[J]. Journal of Electronics & Information Technology, 2016, 38(7): 1660-1665. doi: 10.11999/JEIT151089

全方向M型心動圖運動曲線檢測算法的應(yīng)用研究

doi: 10.11999/JEIT151089
  • 1.

    (廣西民族師范學(xué)院物理與電子工程系 崇左 532200) ②(福州大學(xué)物理與信息工程學(xué)院 福州 350108)

基金項目: 

國家自然科學(xué)基金(61471124)，廣西高校科研項目(YB2014418)

Application of Motion Curve Edge Detection Algorithm in Omni-directional M-mode Echocardiography

  • 1.

    (Department of Physical and Electronic Engineering, Guangxi Normal University for Nationalities, Chongzuo 532200, China)

  • 2.

    (College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China)

Funds: 

The National Natural Science Foundation of China (61471124), The Natural Science Foundation of Guangxi Higher Education Institutions (YB2014418)

  • 摘要: 為了提高全方向M型心動圖運動曲線檢測效果，該文對心動圖的相關(guān)問題進行研究后，提出一種基于模糊增強和灰色理論的全方向M型心動圖運動曲線檢測算法。首先利用改進的模糊增強算法(PAL算法)來抑制噪聲和背景，同時突出邊緣信息；再利用灰色理論中的灰色絕對關(guān)聯(lián)度構(gòu)造統(tǒng)計量來進行邊緣檢測，精確定位出運動曲線；最后通過對孤立的噪聲點和斷裂的邊緣進行后續(xù)的處理，得到最終的運動曲線。實驗結(jié)果表明：該算法檢測效果良好，噪聲魯棒性較強。
    Abstract: In order to improve the detection effect of omni-directional M-mode echocardiography motion curve, this paper focuses on the research of the related issues and proposes an edge detection algorithm with fuzzy enhancement and gray system theory for the omni-directional M-mode echocardiographys motion curve. Firstly, the improved fuzzy enhancement algorithm is used to enhance the edge information, while suppressing the noise and background. Moveover, the proposed algorithm is used to detect edges on echocardiography image based on a ststistic which is constructed by gray correlation in gray system theory. Finally, the best motion edges can be obtained by eliminating noise and connecting crack motion curve. Experimental results show that the proposed algorithm has better accuracy and strong robustness against the noise.
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出版歷程
  • 收稿日期:  2015-09-23
  • 修回日期:  2016-03-15
  • 刊出日期:  2016-07-19

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