Debiasing-Based Noise Suppression for Ultrafast Ultrasound Microvessel Imaging
Debiasing-Based Noise Suppression for Ultrafast Ultrasound Microvessel Imaging
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DOI：
10.1109/tuffc.2019.2918180
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发表时间：
2019-08-01
影响因子：
3.6
通讯作者：
Chen, Shigao
中科院分区：
文献类型：
--
作者：
Huang, Chengwu;Song, Pengfei;Chen, Shigao
基于奇异值分解（SVD）杂波滤波和超快平面波成像相结合的超声微血管成像（UMI）最近证明其多普勒灵敏度显着提高，特别是对于传统多普勒成像不可见的小血管。由于缺乏平面波的发射聚焦，与 SVD 相关的高计算成本和组织深层区域的低血液信噪比 (SNR) 阻碍了 UMI 的实际实施。针对计算成本较高的问题，我们课题组最近提出了一种基于随机SVD（rSVD）和随机空间下采样（rSD）的加速SVD杂波滤波方法，展示了UMI实时实现的可行性。针对深层成像区域的低血流信噪比，我们提出了一种基于噪声去偏的噪声抑制方法，该方法可以轻松应用于加速SVD方法，以弥补实时实现和高成像质量之间的差距。所提出的方法通过使用与常规 UMI 相同的成像序列收集噪声信号来实验性地测量噪声引起的偏差，但超声传输关闭。然后可以从原始功率多普勒 (PD) 图像中减去估计的偏差，以获得有效的噪声抑制。通过体模实验验证了该方法在不同超声成像参数[包括发射电压和时间增益补偿（TGC）设置]下的可行性。与血流模型和体内人体肾脏数据集上的原始 PD 图像相比，去噪图像的 SNR 分别增加了 15.3 dB 和 13.4 dB。所提出的噪声抑制方法的计算成本可以忽略不计，并且可以方便地与先前提出的加速SVD杂波滤波技术相结合，以实现高质量、实时UMI成像。
Ultrasound microvessel imaging (UMI) based on the combination of singular value decomposition (SVD) clutter filtering and ultrafast plane wave imaging has recently demonstrated significantly improved Doppler sensitivity, especially to small vessels that are invisible to conventional Doppler imaging. Practical implementation of UMI is hindered by the high computational cost associated with SVD and low blood signalto- noise ratio (SNR) in deep regions of the tissue due to the lack of transmit focusing of plane waves. Concerning the high computational cost, an accelerated SVD clutter filtering method based on randomized SVD (rSVD) and randomized spatial downsampling (rSD) was recently proposed by our group, which showed the feasibility of real-time implementation of UMI. Concerning the low blood flow SNR in deep imaging regions, here we propose a noise suppression method based on noise debiasing that can be easily applied to the accelerated SVD method to bridge the gap between real-time implementation and high imaging quality. The proposed method experimentally measures the noise-induced bias by collecting the noise signal using the identical imaging sequence as regular UMI, but with the ultrasound transmission turned off. The estimated bias can then be subtracted from the original power Doppler (PD) image to obtain effective noise suppression. The feasibility of the proposed method was validated under different ultrasound imaging parameters [including transmitting voltages and time-gain compensation (TGC) settings] with a phantom experiment. The noise-debiased images showed an increase of up to 15.3 and 13.4 dB in SNR as compared to original PD images on the blood flow phantom and an in vivo human kidney data set, respectively. The proposed noise suppression method has negligible computational cost and can be conveniently combined with the previously proposed accelerated SVD clutter filtering technique to achieve high quality, real-time UMI imaging.