Fast and accurate volume data curvature determination using GPGPU computation

Jacob D. Hauenstein, Timothy S Newman
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Abstract

A methodology for fast determination of a key shape feature in volume datasets using a GPU is described. The shape feature, surface curvature, which is a valuable descriptor for structure classification and dataset registration applications, can be time-consuming to determine reliably by conventional serial computing. The techniques here use parallel processing on a commodity GPU to achieve 100-fold (and above) improvements (for moderate-sized datasets) over conventional serial processing for curvature determination. Techniques for one class of curvature determination methods are detailed, including methods well-suited to datasets acquired by medical scanners.
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使用GPGPU计算快速准确地确定体数据曲率
描述了一种使用GPU快速确定体积数据集中关键形状特征的方法。形状特征曲面曲率是结构分类和数据集配准的重要描述符,但传统的串行计算方法难以可靠地确定曲面曲率。这里的技术在商用GPU上使用并行处理来实现(中等大小的数据集)比传统的曲率确定串行处理100倍(及以上)的改进。详细介绍了一类曲率确定方法的技术,包括非常适合于医学扫描仪获得的数据集的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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