3-D Surfaces Reconstruction Algorithm Optimization For Massive Slice Dataset

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 is complex 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 very complex 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, simplification,combinations 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 massive slice dataset.