用于数字超声成像的嵌入式数字信号处理

M. Hassan, A. Youssef, Y. Kadah
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引用次数: 6

摘要

超声成像是一种高效、无创的医学诊断方法。在FPGA上有效实现嵌入式数字信号处理的数字超声系统,这种小型化使设计具有低功耗、低噪声和轻重量。本文提出了基于FPGA (Xilinx, Inc.)的嵌入式数字超声成像数字信号处理(DSP)。该DSP由FIR希尔伯特变换滤波器组成,利用该滤波器从超声数据的同相分量(I)生成正交分量(Q)。计算接收到的回波的包络(幅度)。该实现已在Virtex-5 FPGA上完成。本工作的目的是利用FIR希尔伯特变换滤波器为超声成像系统构建嵌入式DSP,这将在方法中进行描述。该系统包括:用于重建聚焦超声线的管道加法器块、用于将信号位修改为16位的比特修正块、用于获取正交分量的FIR希尔伯特滤波器块、用于补偿高阶FIR时的延迟的分数阶延迟滤波器(同相滤波器)以及用于计算同相分量和正交分量包络的包络检测块。希尔伯特滤波器以这样的形式实现,即不计算零分接系数,因此L阶滤波器仅使用L/2乘法。这减少了一半的计算时间。FIR希尔伯特滤波器和包络检测的仿真结果接近理想的希尔伯特。与仿真结果相比,实现结果较好。从实现结果来看,估计总功耗为0.8142W,器件利用率可接受。该系统可以接受其他设备进行进一步处理。硬件架构的设计提供了灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embedded digital signal processing for digital ultrasound imaging
Ultrasound imaging is an efficient, noninvasive, method for medical diagnosis. Efficient implementations of digital ultrasound systems on embedded digital signal processing on FPGA, this miniaturization enables a design with low power consumption, low noise, and light weight. This paper proposed embedded digital signal processing (DSP) for digital ultrasound imaging on FPGA (Xilinx, Inc.). The DSP was composed of FIR Hilbert transform filter, which was used to generate Quadrature component (Q) from the In-phase component (I) of the ultrasound data. The envelope (magnitude) of the received echo was computed. The implementation has been done in the Virtex-5 FPGA. The objective of this work is to build embedded DSP for ultrasound imaging system using the FIR Hilbert transform filter, which will be described in the methods. The system was consisted of: the pipeline adder block to reconstruct the focus ultrasound line, the bit modifier block to modify the bit of the signal to 16 bit, the FIR Hilbert filter block to obtain the quadrature components, the fractional delay filter (in-phase filter) to compensate the delay when we were used a high FIR order, and the envelope detection block to compute the envelope of the in-phase and quadrature components. The Hilbert filter is implemented in the form whereby the zero tap coefficients are not computed and therefore an order L filter uses only L/2 multiplications. This was reducing the computational time by a half. The simulation results of FIR Hilbert filter and the envelope detection are near to the ideal Hilbert. The results of the implementation are good compared to the simulation results. From the implementation result the total estimated power consumption equal to 0.8142W and the device utilization was acceptable. It is possible for the system to accept anther devices for further processing. The hardware architecture of the design provided flexibility.
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