基于CUDA架构的改进Marching Cubes算法

计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 573-575.

基于CUDA架构的改进Marching Cubes算法

周筠¹, 蒋富²

湖南财政经济学院信息技术与管理学院长沙410205¹
中南大学信息科学与技术学院长沙410075²

出版日期:2019-02-26 发布日期:2019-02-26
通讯作者: 周筠(1984-),女,博士,讲师,主要研究方向为虚拟现实技术、有限元网格生成方法等,E-mail:jzyf0403@163.com
作者简介:蒋富(1983-),男,博士,副教授,主要研究方向为虚拟现实、医学数据可视化等。
基金资助:
本文受湖南省教育厅科学研究基金项目:虚拟手术仿真系统中的交互式建模技术研究(13C095)资助。

Improved Marching Cubes Based on CUDA

ZHOU Yun¹, JIANG Fu²

Department of Information Management,Hunan University of Finance and Economics,Changsha 410205,China¹
School of Information Science and Engineering,Central South University,Changsha 410075,China²

Online:2019-02-26 Published:2019-02-26

摘要/Abstract

摘要： Marching Cubes是医学体数据可视化的经典算法,但生产的网格质量差、算法执行速度慢成为阻碍其用于数值分析的两个主要缺点。文中提出一种基于硬件加速的Marching Cubes改进算法。该算法采用统一设备架构(CUDA)充分发挥Marching Cubes算法分而治之的优点,利用CUDA的可编程性并行分类体数据,加快了活跃体素和活跃边的提取;同时,该改进算法将得到的活跃边按照中点投影方式进行偏移,从而达到了改善网格质量的目的。最后通过实验表明,该算法可以保证在阈值未知的情况下,进行交互式的高质量网格建模。

关键词: CUDA, Marching Cubes, 医学体数据, 中点投影

Abstract: Marching Cubes (MC) is one of the classical algorithms for medical volume data.But poor mesh quality and slow execution speed have affected the further development such as finite element analysis.In this paper,an improved MC algorithm was presented based on the CUDA.Three kinds of parallel computing were proposed to extract active volumes and edges in the CUDA.Simultaneously,point projection was used in the algorithm to move the endpoints of the active edges and improve the mesh quality.Finally,experimental results show that the presented method can realize the interactive modeling.

Key words: CUDA, Marching Cubes, Medical volume data, Point projection

中图分类号:

TP391

周筠, 蒋富. 基于CUDA架构的改进Marching Cubes算法[J]. 计算机科学, 2018, 45(11A): 573-575. https://doi.org/

ZHOU Yun, JIANG Fu. Improved Marching Cubes Based on CUDA[J]. Computer Science, 2018, 45(11A): 573-575. https://doi.org/

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