Adaptive strain estimation using retrospective processing [medicalUS elasticity imaging]

Lubinski M.A.; Emelianov S.Y.; ODonnell M.

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Adaptive strain estimation using retrospective processing [medicalUS elasticity imaging]

机译：使用回顾性处理的自适应应变估计[医学美国弹性成像]

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Because errors in displacement and strain estimates depend on thenmagnitude of the induced strain, the strain signal-to-noise ratio (SNR)nwill be a function of the applied deformation. If deformation is appliednat the body surface, it is difficult during data acquisition to select ansingle surface displacement providing the highest strain SNR throughoutnthe image. By applying continuous deformation and capturing data innreal-time, the surface displacement providing the highest strain SNR cannbe selected retrospectively. A method to adaptively optimize strain SNRnover the image plane using retrospective processing is presented andndemonstrated with experimental results

机译：因为位移和应变估计中的误差取决于所感应应变的大小，所以应变信噪比（SNR）n将是所施加变形的函数。如果在身体表面上施加了变形，则难以在数据采集过程中选择在整个图像中提供最高应变SNR的单个表面位移。通过连续施加变形并实时捕获数据，无法回顾性地选择提供最高应变SNR的表面位移。提出了一种使用回顾处理在图像平面上自适应优化应变SNRn的方法，并通过实验结果进行了演示。

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《IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control》 |1999年第1期|p.97-107|共11页
作者
Lubinski M.A.; Emelianov S.Y.; ODonnell M.;
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正文语种 eng
中图分类声学工程;计量学;
关键词
acoustic signal processing; adaptive signal processing; biomedical ultrasonics; data acquisition; adaptive strain estimation; applied deformation; continuous deformation; medical US elasticity imaging; retrospective processing; strain signal-to-noise ratio; surfac;

机译：声信号处理;自适应信号处理;生物医学超声;数据采集;自适应应变估计;应用变形;连续变形;医学US弹性成像;回顾性处理;应变信噪比;表面;

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Adaptive strain estimation using retrospective processing [medicalUS elasticity imaging]

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