Khezerloo Solmaz, Rakhmatov Daler
Electrical and Computer Engineering Department, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia, V8P 5C2, Canada.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:444-50. doi: 10.1109/IEMBS.2009.5334787.
Adaptive beamforming can significantly improve the image quality in biomedical ultrasound by reducing the clutter due to interfering signals arriving from undesired directions. We consider the conventional linearly constrained minimum variance (LCMV) adaptive beamformer and propose an alternative based on the well-known generalized sidelobe canceller (GSC) whose adaptation relies on unconstrained gradient-driven optimization. The GSC, coupled with iterative optimization methods, allows for a tradeoff between computational complexity of beamforming and the image quality. To the authors' knowledge, this is the first time a GSC-based gradient-driven approach has been applied and evaluated in the context of ultrasound beamforming.
自适应波束形成可以通过减少来自非期望方向的干扰信号所产生的杂波,显著提高生物医学超声中的图像质量。我们考虑传统的线性约束最小方差(LCMV)自适应波束形成器,并基于著名的广义旁瓣对消器(GSC)提出一种替代方案,其自适应依赖于无约束梯度驱动优化。GSC与迭代优化方法相结合,使得波束形成的计算复杂度与图像质量之间能够进行权衡。据作者所知,这是首次在超声波束形成的背景下应用并评估基于GSC的梯度驱动方法。