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首页> 外文期刊>Ultrasonics, Ferroelectrics and Frequency Control, IEEE Transactions on >Ultrasound time-reversal MUSIC imaging with diffraction and attenuation compensation
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Ultrasound time-reversal MUSIC imaging with diffraction and attenuation compensation

机译：具有衍射和衰减补偿的超声时间反转MUSIC成像

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摘要

Time-reversal imaging with multiple signal classification (TR-MUSIC) is an algorithm for imaging point-like scatterers embedded in a homogeneous and non-attenuative medium. We generalize this algorithm to account for the attenuation in the medium and the diffraction effects caused by the finite size of the transducer elements. The generalized algorithm yields higher-resolution images than those obtained with the original TR-MUSIC algorithm. We evaluate the axial and lateral resolutions of the images obtained with the generalized algorithm when noise corrupts the recorded signals and show that the axial resolution is degraded more than the lateral resolution. The TR-MUSIC algorithm is valid only when the number of point-like targets in the imaging plane is fewer than the number of transducer elements used to interrogate the medium. We remedy this shortcoming by dividing the imaging plane into subregions and applying the TR-MUSIC algorithm to the windowed backscattered signals corresponding to each subregion. The images of all subregions are then combined to form the total image. Imaging results of numerical and phantom data show that when the number of scatterers within each subregion is much smaller than the number of transducer elements, the windowing method yields super-resolution images with accurate scatterer localization. We use computer simulations and tissue-mimicking phantom data acquired with a real-time synthetic-aperture ultrasound system to illustrate the algorithms presented in the paper.
机译：具有多个信号分类的时间反转成像（TR-MUSIC）是一种对嵌入均匀且非衰减介质中的点状散射体成像的算法。我们对该算法进行一般化，以解决介质中的衰减以及由换能器元件的有限尺寸引起的衍射效应。与原始TR-MUSIC算法获得的图像相比，广义算法产生的图像分辨率更高。当噪声破坏记录的信号时，我们评估了用通用算法获得的图像的轴向和横向分辨率，并表明轴向分辨率比横向分辨率下降得更多。仅当成像平面中点状目标的数量少于用于询问介质的换能器元件的数量时，TR-MUSIC算法才有效。我们通过将成像平面划分为多个子区域并将TR-MUSIC算法应用于与每个子区域相对应的加窗后向散射信号来解决此缺点。然后将所有子区域的图像合并以形成总图像。数值和幻像数据的成像结果表明，当每个子区域内的散射体数量远小于换能器元件的数量时，加窗方法会生成具有精确散射体定位的超分辨率图像。我们使用计算机仿真和通过实时合成孔径超声系统获取的模拟组织幻象数据来说明本文中介绍的算法。

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