融入背景差分连续重构的心脏医学图像重建  

Heart Medical Image Reconstruction Based on Background Difference Continuous Reconstruction

作　　者：赵志升[1] 张晓[1] 梁俊花[1] 叶永飞[1] 

机构地区：[1]河北北方学院信息科学与工程学院,河北张家口075000

出　　处：《科技通报》2015年第8期207-209,共3页Bulletin of Science and Technology

基　　金：河北省高等学校科学技术研究重大项目(ZD20131085);河北北方学院重大课题(ZD201301)

摘　　要：通过对人体心脏器官的医学图像重建,为实现三维可视化手术及图像重构提供图像基础。传统的心脏医学图像重建方法采用的是三维坐标点动态数据采集算法,当测量点相对散乱时无法满足心脏器官重建的准确性要求。提出一种融入背景差分连续重构的心脏医学图像重建方法,进行图像细节纹理的灰度化图像进行提升分离,定义表面渲染的选项,计算二维层状图像纹理特征像素点检测沿幅角方向上模值的极大值点,得到三维成像的仿真视景图像的质心位置,采用二阶累积泰勒展开算法,对三维图像模型进行心脏图像的纹理特征提取,实现算法改进。仿真结果得出,采用该算法进行心脏医学图像重建,重建表面的最大误差显著减少,重建精度较高,重建时间减少,在实时性和精确性上性能优越。The medical image on human cardiac tissue reconstruction image, providing foundation for the realization of three-dimensional visualization operation and image reconstruction. The cardiac medical image reconstruction of the traditional method is the 3D coordinates of points of dynamic data collection algorithm, it cannot meet the requirements of heart organ reconstruction accuracy when measuring point when relatively scattered. Put forward a kind of blend into the background difference heart medical image reconstruction method divides the continuous reconstruction, grayscale image tex- ture to improve the separation, the definition of surface rendering options, maximum value calculation of two-dimensional layered image texture feature pixel point detection direction along the argument module value, get the simulation of 3D imaging visual image centroid position, using two order cumulant Taylor expansion algorithm, texture feature extraction for cardiac image of 3D image model, the improved algorithm,. Simulation results show that using the algorithm for cardiac medi- cal image reconstruction, the maximum error of the reconstructed surface reconstruction precision, significantly reduce the reconstruction time is reduced, in real time and accuracy of superior performance.

关 键 词：背景差分 医学图像 重构 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]