摘要
弹性成像能够检测组织的弹性信息,进而描述组织生理、病理状态,对疾病的检测和诊断具有重要的应用价值。为了改善二维弹性算法的轴向分辨率,本文对一维和二维弹性成像算法进行了比较研究,提出一种基于加权相位分离和二维互相关的混合位移估计算法,首先利用二维时域互相关技术进行粗估计,然后再利用加权相位分离技术(WPS)对结果进行精估计。同时,通过仿真和仿体实验对算法的精确性和效率进行了验证。结果表明,算法具有较好的鲁棒性,能够有效地提高运行效率和图像信噪比,上述研究对高性能弹性成像系统的研究与设计具有重要的指导意义。
Elastography is an imaging method which is able to display the distribution of elastic properties of soft tissue,and provide valuable diagnostic information.In this paper,we compared 1D motion estimation with 2D motion estimation for elastography and present a framework combined with weighted phase separation（WPS）and 2Dcross-correlation for displacement estimation.2Dcross-correlation was first applied to the RF signals and then used WPS method to calculate a more precision axial displacements.We also compared the images qualities and efficiency of 1Dalgorithm and 2Dalgorithm by simulations and phantom experiments.It is shown that our method is fast and robust to relatively complex tissue motions and could improve SNRe.This method will have some poetical for the latter experiments and clinical applications.
出处
《影像科学与光化学》
CAS
CSCD
北大核心
2016年第1期102-110,共9页
Imaging Science and Photochemistry
基金
国家自然科学基金青年科学基金(11204198)
中科院百人计划(Y223011302)
国家科技支撑计划(2012BAI13B02)
苏州市科技计划项目(Y539021903)资助
关键词
弹性成像
运动估计
二维互相关
先验估计
加权相位分离
elstography
motion estimation
2Dcross-correlation
prior estimation
weighted phase separation
