基于Cell BE的医学体数据集快速等值面提取

Hai Jin, Bo Li, Ran Zheng, Qin Zhang
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引用次数: 2

摘要

由于医学成像模式和计算技术的巨大进步,医学成像和科学模拟产生的体积数据的大小显着增加。体积数据通常需要可视化,行军立方体算法(Marching Cubes algorithm,简称MC)是医学应用中等值面提取的标准方法之一。然而,MC算法需要大量的数据计算能力。Cell宽带引擎(Cell)处理器是一种典型的COTS(现成的商品)异构处理器,用于处理极其苛刻的计算,可用于加速医疗应用中的等值面提取。本文提出了一种基于流模型的MC算法到Cell的高效映射方案。具体来说,在PPE上运行基于块的过滤器作为预处理阶段,以避免不必要的数据传输和计算,MC内核作为后续阶段在spe上运行。通过调优块的大小,可以协调PPE和SPE的工作负载。实验结果表明,与传统的重铁cpu相比,整体等面提取速度提高了10倍以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Isosurface Extraction for Medical Volume Dataset on Cell BE
The size of volumetric data generated by medical imaging and scientific simulations is increased significantly due to the dramatic advances in medical imaging modalities and computing technologies. The volumetric data generally need to be visualized and Marching Cubes algorithm (MC for short) is one of the standard methods of the isosurface extraction for the medical applications. However, MC algorithm requires a large amount of data computing power. The Cell Broadband Engine (Cell for short) processor, which is a typical COTS (commodity off-the-shelf) heterogeneous designed to handle extremely demanding computations, can be used to hasten isosurface extraction in medial application. In this paper, we present a streaming model-based scheme to efficiently map MC algorithm to Cell. Specifically, a block-based filter running on PPE is imposed as a preprocessing stage to avoid unnecessary data transfer and computation, and the MC kernel runs on SPEs as the subsequent stage. Through tuning the size of the block, the workload of PPE and SPE is orchestrated harmoniously. The experimental results demonstrate that overall isosurface extraction speedup of more than 10 times is achieved compared with conventional heavy iron CPUs.
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