用FPGA实现的耦合滤波方法

C. Zhang, Tianzhu Liang, P. Mok, Weichuan Yu
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引用次数: 5

摘要

在超声图像分析中,散斑跟踪方法被广泛应用于研究人体组织的弹性。然而,“特征-运动去相关”仍然是散斑跟踪方法面临的挑战。最近提出了一种耦合滤波方法,用于在组织变形较大时准确估计应变值。新方法的主要缺点是计算复杂度高。即使是基于gpu的程序也需要几个小时才能完成分析。在本文中,我们提出了一个基于fpga的实现来进一步加速。讨论了该方法中fpga处理不同图像处理元件的能力。为了在FPGA上构建高效的流水线,对算法进行了重新表述。在Xilinx Virtex-7 FPGA上的最终实现比在两个NVIDIA显卡(GeForce GTX 580)上的GPU实现快15倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FPGA implementation of the coupled filtering method
In ultrasound image analysis, speckle tracking methods are widely applied to study the elasticity of body tissue. However, “feature-motion decorrelation” still remains as a challenge for speckle tracking methods. Recently, a coupled filtering method was proposed to accurately estimate strain values when the tissue deformation is large. The major drawback of the new method is its high computational complexity. Even the GPU-based program requires a few hours to finish the analysis. In this paper, we propose an FPGA-based implementation for further acceleration. The capability of FPGAs on handling different image processing components in this method is discussed. The algorithm is reformulated to build a highly efficient pipeline on FPGA. The final implementation on a Xilinx Virtex-7 FPGA is 15 times faster than the GPU implementation on two NVIDIA graphic cards (GeForce GTX 580).
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