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全方向M型心动图运动曲线检测算法的应用研究

王琨 黄立勤 郑鑫

王琨, 黄立勤, 郑鑫. 全方向M型心动图运动曲线检测算法的应用研究[J]. 电子与信息学报, 2016, 38(7): 1660-1665. doi: 10.11999/JEIT151089
引用本文: 王琨, 黄立勤, 郑鑫. 全方向M型心动图运动曲线检测算法的应用研究[J]. 电子与信息学报, 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型心动图运动曲线检测算法的应用研究

doi: 10.11999/JEIT151089
基金项目: 

国家自然科学基金(61471124),广西高校科研项目(YB2014418)

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

Funds: 

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

  • 摘要: 为了提高全方向M型心动图运动曲线检测效果,该文对心动图的相关问题进行研究后,提出一种基于模糊增强和灰色理论的全方向M型心动图运动曲线检测算法。首先利用改进的模糊增强算法(PAL算法)来抑制噪声和背景,同时突出边缘信息;再利用灰色理论中的灰色绝对关联度构造统计量来进行边缘检测,精确定位出运动曲线;最后通过对孤立的噪声点和断裂的边缘进行后续的处理,得到最终的运动曲线。实验结果表明:该算法检测效果良好,噪声鲁棒性较强。
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出版历程
  • 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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