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Parallel 2D FFT implementation on FPGA suitable for real-time MR image processing

机译:适用于实时MR图像处理的FPGA并行2D FFT实现

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摘要

We report the design and implementation of a parallel two-dimensional fast Fourier transform (2D FFT) algorithm on a Field Programmable Gate Array (FPGA) for real-time MR image processing. Although a number of architectures of 2D FFT hardware processors have been reported, these generic processors or IP cores are not always effective for processing MRI data. The key feature of our design is that our processors are customized solely for real-time MRI applications. We demonstrate that by considering the unique features of real-time MRI data streams, we were able to develop and implement the 2D FFT processors that are resource-efficient and flexible enough to handle both regular and irregular data. Using a data-driven approach, we were able to simplify the inter-processor data communication while maintaining data synchronization without a synchronous clock signal bus and complex interconnection network. We experimentally verified our designs by processing multi-slice image data sets with 128 × 128 and 256 × 256 in-plane resolution. The results demonstrate the effectiveness of our 2D FFT processors and show that image reconstruction can be accelerated in proportion to the parallel processing factor. We achieved image-reconstruction processing rates up to 3000 and 800 slices per second for images with 128 × 128 and 256 × 256 in-plane resolution, respectively. The results also indicate that the image-reconstruction acceleration is primarily limited by the speed of the data transfer between the FPGA device and external sensors.
机译:我们报告了在现场可编程门阵列(FPGA)上用于实时MR图像处理的并行二维快速傅里叶变换(2D FFT)算法的设计和实现。尽管已经报道了许多2D FFT硬件处理器的体系结构,但是这些通用处理器或IP内核对于处理MRI数据并不总是有效的。我们设计的关键特征是我们的处理器是专门为实时MRI应用而定制的。我们证明,通过考虑实时MRI数据流的独特功能,我们能够开发和实现2D FFT处理器,这些处理器资源高效且足够灵活,可以处理常规和非常规数据。使用数据驱动的方法,我们能够简化处理器间的数据通信,同时保持数据同步,而无需同步时钟信号总线和复杂的互连网络。我们通过处理面内分辨率为128×128和256×256的多层图像数据集,通过实验验证了我们的设计。结果证明了我们的2D FFT处理器的有效性,并表明可以与并行处理因子成比例地加速图像重建。对于面内分辨率为128×128和256×256的图像,我们分别实现了高达3000和800切片每秒的图像重建处理速率。结果还表明,图像重建加速主要受FPGA器件与外部传感器之间数据传输的速度限制。

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