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Computationally Efficient Time-Recursive IAA-Based Blood Velocity Estimation

机译:基于IAA的计算有效时间递归的血流速度估计

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摘要

High-resolution spectral Doppler is an important and powerful noninvasive tool for estimation of velocities in blood vessels using medical ultrasound scanners. Such estimates are typically formed using an averaged periodogram technique, resulting in well-known limitations in the resulting spectral resolution. Recently, we have proposed techniques to instead form high-resolution data-adaptive estimates exploiting measurements along both depth and emission. The resulting estimates gives noticeably superior velocity estimates as compared to the standard technique, but suffers from a high computational complexity, making it interesting to formulate computationally efficient implementations of the estimators. In this work, by exploiting the rich structure of the iterative adaptive approach (IAA) based estimator, we examine how these estimates can be efficiently implemented in a time-recursive manner using both exact and approximate formulations of the method. The resulting algorithms are shown to reduce the necessary computational load with several orders of magnitude without noticeable loss of performance.
机译:高分辨率频谱多普勒仪是使用医用超声扫描仪评估血管速度的重要而强大的非侵入性工具。通常使用平均周期图技术来形成这样的估计,从而导致所得到的光谱分辨率受到众所周知的限制。最近,我们提出了利用沿深度和发射方向的测量结果来形成高分辨率数据自适应估计的技术。与标准技术相比,所得的估计值给出了明显更好的速度估计值,但遭受了很高的计算复杂度,使得制定估计值的计算有效实现方式变得很有趣。在这项工作中,通过利用基于迭代自适应方法(IAA)的估计器的丰富结构,我们研究了如何使用该方法的精确公式和近似公式以时间递归的方式有效地实现这些估计。结果表明,所得算法可将所需的计算量减少几个数量级,而不会显着降低性能。

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