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Component-Based Modeling and Processing of Medical Ultrasound Signals

机译:基于组件的医学超声信号建模与处理

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Component-based modeling and processing can be found in many signal and image processing applications. In this paper, we apply this approach to cardiac medical ultrasound imaging. We show how the raw data generated in the ultrasound scanning process can be modeled as consisting of two distinct components. By decomposing these signals into the two components, we are able to apply separate processing pipelines tailored to each component. The potential benefits of this approach to medical ultrasound imaging are demonstrated in two central issues of the commonly used processing: 1) the very large amounts of data generated by the scanning process, and 2) artifacts in the images and videos generated by standard processing, commonly referred to as side lobe artifacts. We manage to compress the data by a factor of over 20 as well as remove the side lobe artifacts. These benefits are demonstrated on both simulated data and real cardiac scanning data.
机译:基于组件的建模和处理可以在许多信号和图像处理应用程序中找到。在本文中,我们将这种方法应用于心脏医学超声成像。我们展示了如何将超声扫描过程中生成的原始数据建模为由两个不同的组件组成。通过将这些信号分解为两个组件,我们可以应用针对每个组件量身定制的单独处理管道。常用处理的两个主要问题证明了这种方法在医学超声成像中的潜在优势:1)扫描过程生成的大量数据,以及2)标准处理生成的图像和视频中的伪影,通常称为旁瓣伪影。我们设法将数据压缩20倍以上,并消除了旁瓣伪像。这些好处在模拟数据和实际心脏扫描数据上都得到了证明。

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