文档介绍：华中科技大学硕士学位论文
摘

要
MC(Marching Cubes)算法作为一种经典的三维重建算法,得到了广泛的应用。
但针对海量断层数据,采用 MC 算法进行三维重建时,存在很多问题:如拓扑关系
的求解,算法程序效率的提高等等。因此,三维重建算法的优化问题便成为当前研
究的一个热点。
文章首先介绍 MC 算法的基本原理与实现流程,然后介绍采用 MC 算法进行三
维重建的主要流程,并简单介绍了构网、平滑、简化、合并这几个关键步骤。其中,
平滑、简化、合并这三个步骤都是基于包含拓扑信息的网格数据进行的,因此需要
对传统的构网算法实施改进:使之能够在构网的同时同步取得各三角面片间的拓扑
关系。
拓扑关系的取得,比较有效的方法是边构网边获取,但对于海量断层数据,这
一方法面临计算资源与计算规模之间的矛盾,为了解决这一矛盾,文章提出了“双
缓存、三层交换”的方法对构网关键算法进行优化,使得算法程序既能满足海量断
层数据处理的要求,又能满足算法程序性能的要求。文章着重分析了这一方法的机
理与实现流程,最后结合实际数据对算法程序性能进行对比分析,得出结论。
从结论分析可以得出,针对海量断层数据处理,利用 MC 算法进行三维重建时,
“双缓存、三层交换”的机制确实能在一定程度上给算法程序的性能带来提升,能
够达到优化算法的目的。
关键词: MC 算法优化

三维重建

双缓存

三层交换
I
华中科技大学硕士学位论文
Abstract
MC (Marching Cubes) is a popular 3-D surfaces reconstruction algorithm. But for
huge segment datasets, thers is many problems for this typical algorithm, such as realized
method plex and performance of algorithm program is inefficient. So how to
improve the effect of the algorithm program is a hot topic.
Because the data used for reconstruction is very huge, the reconstruction and its
optimizing operation base on these data is plex and inefficient. So it’s very
important to study 3-D surfaces reconstruction algorithm optimization.
This paper introduces the basic principles of MC algorithm and implementation
processes firstly. Secondly, it introduces the key steps of digital virtual human 3-D
surfaces reconstruction using MC algorithm, which includes reconstruction,smooth,
binations and so on. The implementation of last three steps bases on
the topological relationship of the triangles,so we must obtain the topological relationship
of triangles while reconstructing.
The more effective method of obtaining the triangles topological relationship is
computing while creating triangles. But for massive slice dataset processing,this method
is inefficient. In order to solve this problem,this paper presents a "double cache,three
layer switching "method. Practice shows it can make a high performance while processing