In this work, a novel technique for real-time clutter rejection in ultrasound Color Flow Imaging (CFI) is proposed. Suppressing undesired clutter signal is important because clutter prohibits an unambiguous view of the vascular network. Although conventional eigen-based filters are potentially efficient in suppressing clutter signal, their performance is highly dependent on proper selection of a clutter to blood boundary which is done manually. Herein, we resolve this limitation by formulating the clutter suppression problem as a foreground-background separation problem to extract the moving blood component. To that end, we adapt the fast Robust Matrix Completion (fRMC) algorithm, and utilize the in-face extended Frank-Wolfe method to minimize the rank of the matrix of ultrasound frames. Our method automates the clutter suppression process, which is critical for clinical use. We name the method RAPID (Robust mAtrix decomPosition for suppressIng clutter in ultrasounD) since the automation step can substantially streamline clutter suppression. The technique is validated with simulation, flow phantom and two sets of in-vivo data. RAPID code as well as most of the data in this paper can be downloaded from http://rapid.sonography.ai.

中文翻译：

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用于实时抑制杂波的超声彩色流图像的低秩和稀疏分解。

在这项工作中，提出了一种用于超声彩色流成像（CFI）中实时杂波抑制的新技术。抑制不希望的杂波信号很重要，因为杂波会阻止对血管网络的清晰观察。尽管常规的基于特征的滤波器在抑制杂波信号方面可能非常有效，但其性能高度依赖于手动选择杂波到血液边界的正确选择。在此，我们通过将杂波抑制问题公式化为提取运动血液成分的前景背景分离问题来解决此限制。为此，我们采用了快速鲁棒矩阵完成（fRMC）算法，并采用了面内扩展Frank-Wolfe方法来最小化超声帧矩阵的等级。我们的方法使杂波抑制过程自动化，这对于临床使用至关重要。我们将方法命名为RAPID（用于抑制超声中杂波的鲁棒mAtrix分解），因为自动化步骤可以大大简化杂波抑制。该技术已通过仿真，体模和两组体内数据进行了验证。RAPID代码以及本文中的大多数数据可以从http://rapid.sonography.ai下载。