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Orthogonal matching pursuit compressive sampling matching pursuit for Doppler ultrasound signal reconstruction

机译:正交匹配追踪和压缩采样匹配追踪的多普勒超声信号重建

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In this work we want to make use of a novel framework of compressed sensing (CS) sampling theory to reconstruct the Doppler ultrasound signal. CS aim to reconstruct signals and images from significantly fewer measurements. Doppler ultrasound is one of the most non-invasive diagnostic techniques. The present data acquisition methods use much data to acquire the image, this cause in increasing the process time and heating. To overcome this limitation we propose a framework of CS. The result shows that the reconstruction performed perfectly with high quality in very short time, by using two CS reconstruction algorithms, orthogonal matching pursuit and compressive sampling matching pursuit algorithms. There is no significant difference in the quality of the resulting images reconstructed by using both reconstruction algorithms.
机译:在这项工作中,我们希望利用压缩感知(CS)采样理论的新颖框架来重建多普勒超声信号。 CS旨在通过明显减少的测量来重建信号和图像。多普勒超声是最无创的诊断技术之一。当前的数据获取方法使用大量数据来获取图像,这导致增加处理时间和加热。为了克服此限制,我们提出了CS的框架。结果表明,通过使用两种CS重建算法,正交匹配追踪和压缩采样匹配追踪算法,可以在非常短的时间内以高质量完美地进行重建。使用这两种重建算法重建的结果图像的质量没有显着差异。

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