High-resolution and high-sensitivity blood flow estimation using optimization approaches with application to vascularization imaging

H. Shen, C. Barthélémy, E. Khoury, Y. Zemmoura, J. Remeniéras, A. Basarab, Denis Kouamé
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引用次数: 8

Abstract

In this paper, we address the problem of high-resolution flow estimation in medical ultrasound images. Imaging methods based on ultrafast sequences associated with adaptive spatiotemporal SVD clutter filtering have recently improved blood flow detection. Herein, we investigate a new way of addressing the clutter filtering problem in order to obtain a high-resolution flow estimation, through solving an inverse problem corresponding to both deconvolution and robust principal component analysis. Applied to tissue vascularization imaging via power Doppler images, the proposed method highlights finer details on experimental data compared to existing approaches.
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基于优化方法的高分辨率和高灵敏度血流估计及其在血管化成像中的应用
本文主要研究医学超声图像的高分辨率流估计问题。基于超快序列和自适应时空奇异值分解杂波滤波的成像方法近年来改进了血流检测。在此,我们研究了一种新的方法来解决杂波滤波问题,以获得高分辨率的流量估计,通过解决反卷积和鲁棒主成分分析对应的逆问题。应用于组织血管化成像的功率多普勒图像,与现有的方法相比,该方法突出了实验数据的更精细的细节。
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