基于多尺度融合和相关性分析的全方向M型心动图优化研究

Optimization of Onmi-directional M-mode Cardiography Based on Multi-scale Integration and Correlation Analysis

针对全方向M型心动图在对目标运动曲线检测过程因虚假边缘点而存在误检问题进行研究,在充分分析全方向M型心动图特点的基础上,设计一种结合多尺度融合和相关性分析的全方向M型心动图检测算法。该算法首先通过构建小波函数在不同的固定尺度空间下进行运动曲线检测,然后对不同尺度下检测出的运动曲线进行融合,最后结合心脏运动的相关性信息生成正确的运动曲线。通过LEJ-2型全方向M型系统的实验表明,该算法能自动去除全方向M型心动图中目标运动曲线的虚假边缘、无关噪声等干扰,同时准确保留有用信息,从而大大减轻系统的人工干预程度,实现了对国家发明专利"全方向M型心动图方法及其系统98 125713.5"系统的优化设计。

This paper studied on motion curve optimization of onmi-directional M-mode cardiography.A detection algorithm was designed based on a combination of multi-scale integration and correlation analysis after a full analysis of all the characteristic of onmi-directional M-mode cardiography.Firstly the motion curve was detected by constructing wavelet function at different spatial scales,then the motion curves of different spatial scales were integrated.Finally the correct motion curve was generated combined with the cardiac motion information.The experiment by LEJ-2 onmi-directional M-mode cardiography showed the algorithm could automatically remove the false edge,noise of onmi-directional M-mode cardiography,keep accurate and useful information,thus greatly reduced the human intervention.The optimal design of the state invention patents ＂the onmi-directional M-mode cardiography and its system 98 125713.5＂ was realized.