A Sparse regularization approach for ultrafast ultrasound imaging
A Sparse regularization approach for ultrafast ultrasound imaging
复制标题
超快超声成像的稀疏正则化方法
DOI：
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发表时间：
2015
期刊：
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通讯作者：
O. Bernard
中科院分区：
文献类型：
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作者：
R. Carrillo;Adrien Besson;Miaomiao Zhang;D. Friboulet;Y. Wiaux;J. Thiran;O. Bernard
基于平面波消噪的超快成像技术由于具有高帧率的特点而成为研究的热点。提出了几种基于傅里叶域重构或延迟和重构的方法。使用单个PW，与具有聚焦光束的经典DAS方法相比，这些技术在分辨率和对比度方面的质量较低。为了克服这一缺点，需要复合多个定向pw，这降低了目前此类技术可以达到的高帧率限制。基于压缩感知（CS）框架，我们提出了一种新的方法，以增加重建时的计算复杂度为代价，只需要1 PW就可以重建高质量的超声图像。
Ultrafast imaging based on plane-wave (PW) insonification is an active area of research due to its capability of reaching high frame rates. Several approaches have been proposed either based on either of Fourier-domain reconstruction or on delay-and-sum (DAS) reconstruction. Using a single PW, these techniques achieve low quality, in terms of resolution and contrast, compared to the classic DAS method with focused beams. To overcome this drawback, compounding of several steered PWs is needed, which currently decreases the high frame rate limit that could be reached by such techniques. Based on a compressed sensing (CS) framework, we propose a new method that allows the reconstruction of high quality ultrasound (US) images from only 1 PW at the expense of augmenting the computational complexity at the reconstruction.