基于CUDA架构的改进Marching Cubes算法  

Improved Marching Cubes Based on CUDA

作　　者：周筠 蒋富[2] ZHOU Yun;JIANG Fu(Department of Information Management,Hunan University of Finance and Economics,Changsha 410205,China;School of Information Science and Engineering,Central South University,Changsha 410075,China)

机构地区：[1]湖南财政经济学院信息技术与管理学院,长沙410205 [2]中南大学信息科学与技术学院,长沙410075

出　　处：《计算机科学》2018年第B11期573-575,共3页Computer Science

基　　金：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

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。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.

关 键 词：医学体数据 MARCHING CUBES CUDA 中点投影 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]