多普勒超声信号重构中的正交匹配追踪与压缩采样匹配追踪

S. M. S. Zobly, Y. Kadah
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引用次数: 14

摘要

在这项工作中,我们希望利用压缩感知(CS)采样理论的新框架来重建多普勒超声信号。CS的目标是从更少的测量中重建信号和图像。多普勒超声是最无创的诊断技术之一。目前的数据采集方法需要大量的数据来获取图像,这增加了处理时间和加热。为了克服这一限制,我们提出了一个CS框架。结果表明,采用正交匹配追踪算法和压缩采样匹配追踪算法两种CS重建算法,在很短的时间内完成了高质量的重建。两种重建算法重建的结果图像质量没有显著差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orthogonal matching pursuit & compressive sampling matching pursuit for Doppler ultrasound signal reconstruction
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.
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