Optimization For Omni-directional M-mode Echocardiography Detection And Its Application

As the most important organs of the human body, the healthy of heart affect the human’s life. Therefore, the detection of the heart’s dynamic information to analysis the myocardial disease is an important topic in the life sciences. Biomedical Engineering Institute of Fuzhou University has developed a omni-direction M-mode echocardiography system, It extract the heart’s dynamic information from the ultrasound cardiac image sequences with the help of computer and image processing technology. The clinical studies have shown that it have auxiliary function of the diagnosis of the cardiac disease. This article supported by the Fujian natural science foundation project(2011J01268), Fujian main science and technology project (2011H0027) and 7th framework programme(FP7). This article focus on accurate detection research of omni-directional M-mode echocardiography’s motion curve and the improvement of the new issues raised in the clinical application, the major contents are concluded as follows:(1) This article have designed a new method for the detection of omni-directional M-mode echocardiography’s motion curve which also called image edge. Detection of the motion curve is the core of the omni-directional M-mode echocardiography system, the accuracy of motion curve is affect the availability of the dynamic information of the heart. This article focus on the research of the medical image edge detection, by read the domestic and foreign literature, Analyze and summarize of some classic medical image edge detection techniques. In order to achieve the real-time, accuracy and clinical useful of the detection of the motion curve, this article proposed a multi-scale adaptive edge detection method based on contourlet transform. Firstly it uses the local entropy-based algorithm to divide the image into images at different scales. Secondly the edges of the images are extracted in the space of a single scale with the help of the wavelet transform modulus maxima method. Finally it integrates the edge curves under different scale spaces with a compensation link method to get the best motion edges. Experimental results show that the detection method can reduce the manual intervention in the original system, it provide a good foundation for the subsequent detection of the cardiac dynamic information.(2) This article have designed a method for improving the accuracy of the dynamic information. In view of the characteristics of the omni-directional M-mode echocardiography, this article reasonably corrected the operator of first-order differential and second-order differential which used to obtain the velocity and acceleration of the heart’s movement, while it used Marple algorithm to analysis the power spectrum of the heart’s movement. In addition, this subject proposed a solution based on the area filter to improve the accuracy of the dynamic information. Firstly analysis the differences in different regions on echocardiography which reflected by the relevant information of the cardiac cycle, on this basis, it research the specific method of region filter from the selection of the filter and the determination of the low-pass cutoff frequency. Experimental results show that the method effective suppression the amplification of image pixel noise caused by the differential operation which the calculation of the velocity and acceleration should used.Finally, the experiment is carried out on LEJ-2 omni-directional M-mode echocardiography system developed by Fuzhou University Biomedical Engineering Institute. This article provide detailed experimental data and results analysis, it show that the research method is effective.