Open ultrasound platforms foster the development of novel image processing techniques due to its flexibility in terms of both software and hardware updates. There is a growing need for rapid prototyping and modelling platforms can be used to develop high-level applications, such as MATLAB/Simulink. Although there are several model-based methods for ultrasound imaging described in the literature, most of them focus on specific digital signal processing stages, and there is little assessment of the simulation environment of Model Composer and System Generator for Xilinx Field-programmable Gate Arrays (FPGA). The purpose of this article is to implement the steps of an ultrasound reception beamforming using the delay and sum technique for B-mode imaging, and then comparing the results between a reference MATLAB script and the results from Xilinx based-model implemented in Simulink environment. The simulation uses 12-bit ultrasound data sampled at 40 MHz from a phantom acquired with a 128-element transducer with an aperture of 8 elements. The design was synthesized for a Xilinx Zynq 7000 FPGA. The qualitative results of the generated B-mode imagens are in excellent agreement, with a CNR error of 0.01, and a processed envelope with NRMSE of 0.085%. In conclusion, the use of tools such as Model Composer and system generator proved to be adequate for rapid prototyping and yields very accurate results for FPGA simulations when compared to MATLAB calculations.
KEYWORDS: Digital signal processing, Field programmable gate arrays, Data modeling, Apodization, Phased arrays, Signal processing, Model-based design, Ultrasonography, Data conversion, Finite impulse response filters
In this paper we present a model-based Field Programmable Gate Array (FPGA) design flow for ultrasound imaging using the delay-and-sum (DAS) beamforming technique. The beamformer model is based on DSP Builder toolbox in the Matlab/Simulink environment, used for fast prototype design and automatic hardware description language code generation for Intel FPGAs. The design was synthesized for an Intel Stratix IV FPGA and implemented on a Terasic DE4- 230 board, including the following digital signal processing steps: digital filtering, focusing delay adjustment, apodization, coherent summation, envelope detection and logarithmic compression. To evaluate our model, we used raw radiofrequency data from a phantom acquired using a 128-element convex transducer (2-5 MHz) with an active aperture of 8 elements. A Nios II processor was integrated into the FPGA to send and receive data from the model and transmit them to the host computer for off-line scan conversion and B-mode image generation. The results show that the proposed strategy is efficient for rapid prototyping of FPGA devices in ultrasound imaging applications. The overall FPGA resources utilization was less than 15%, indicating that other digital signal processing algorithms, such as interpolation, decimation, and scan conversion, can be implemented using this design methodology in both medical and non-destructive imaging applications.
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