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In vivo investigation of filter order influence in eigen-based clutter filtering for color flow imaging

机译:基于特征杂波滤波的彩色血流成像中滤波器阶次影响的体内研究

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摘要

Eigen-based adaptive filters have shown potential for providing a superior attenuation of clutter in color flow imaging. Critical for the success of this technique is the correct selection of filter order. In this work we review and compare filter order selection schemes for eigen-based filters in an in vivo context. Data was acquired from a thyroid tumor (PRF = 250 Hz, ensemble size = 12), where substantial tissue movement was present due to carotid artery pulsations, respiratory movements, and probe navigation. Eigen-filtering performance was evaluated for 1) an eigenvalue spectrum threshold, 2) a threshold on the ratio of successive eigenvalues, and 3) a threshold on eigenvector mean frequency estimated by the autocorrelation approach. Based on the observed eigenvalue and eigen-frequency distributions in analytical and in vivo examples, all filter order algorithms investigated suffered from potential pitfalls in specific Doppler scenarios. In the in vivo examples, the fixed order eigenfilter gave a sufficient suppression of clutter, but also removed substantial blood signal. Thresholding the ratio of eigenvalues better retained signal from blood, but also spurious artifacts was observed. The most consistent results were achieved by thresholding the mean frequency of the eigenvectors. The results demonstrate that given a suitable filter order algorithm, robust filtering can be achieved with the eigen-based approach. © 2007 IEEE.
机译:基于本征的自适应滤波器已显示出在色流成像中提供出色的杂波衰减的潜力。该技术成功的关键是正确选择滤波器的阶数。在这项工作中,我们将审查和比较体内环境中基于特征的过滤器的过滤器顺序选择方案。数据来自甲状腺肿瘤(PRF = 250 Hz,集合大小= 12),该组织由于颈动脉搏动,呼吸运动和探头导航而存在大量组织运动。对特征滤波性能进行了评估:1)特征值谱阈值,2)连续特征值之比的阈值,以及3)通过自相关方法估算的特征向量平均频率的阈值。根据在分析和体内示例中观察到的特征值和特征频率分布,研究的所有滤波器阶数算法在特定的多普勒场景中都存在潜在的陷阱。在体内的例子中,固定顺序的特征滤波器对杂波具有足够的抑制作用,但也消除了实质性的血液信号。阈值特征值的比率可以更好地保留来自血液的信号,但也可以观察到伪像。通过对特征向量的平均频率进行阈值处理,可以获得最一致的结果。结果表明,给定合适的滤波器阶数算法,可以使用基于特征的方法实现鲁棒滤波。 ©2007 IEEE。

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    Lovstakken L; Yu ACH; Torp H;

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  • 年度 2007
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  • 正文语种 eng
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