从表面重构的体数据实现3维网格剖分

目的 针对有限元分析中网格最优化问题,提出一种改进的生成四面体网格的自组织算法。方法 该算法首先应用几何方法将三角形表面模型重新构造成规定大小的分类体数据,同时由该表面模型建立平衡八叉树,计算用以控制网格尺寸的3维数组;然后将体数据转换成邻域内不同等值面的形态一致的边界指示数组;结合改进的自组织算法和相关3维数据的插值函数,达到生成四面体网格的目的。结果 实验结果对比表明,该方法能够生成更高比例的优质四面体,增强了对扁平面体的抑制能力,同时很好地保证了边界的一致。结论 在对封闭的3维表面网格进行有限元建模时,本文算法为其提供了一种有效、可靠的途径。     

基于特征保持的三维模型四面体化及优化

三维模型四面体化是一种重要的有限元网格生成技术.介绍了一种特征保持的四面体网格生成及优化算法.首先使用三维模型主成分分析进行预处理,然后用体心立方构建初始四面体,接着通过拉普拉斯坐标改变模型边界切点的移动方式保持模型的局部特征,最后构造改进的密度能量误差函数优化四面体网格质量.实验结果表明,该方法可行、有效,且能很好地保持模型特征.     

基于医学体数据生成四面体网格的方法

为了从医学体数据直接构造四面体网格,提出一种基于栅格的网格生成算法.该算法的主要思想是从背景栅格中提取并填充代表区域边界的等值面.首先,对医学体数据进行预处理与采样,构建一个背景栅格.其次,用对偶方法从栅格提取三角表面网格,用于分段线性逼近等值面.然后,对栅格中所有位于等值面之内或与等值面相交的立方体,用预定义的模板分解成四面体单元.最后,用Laplacian平滑技术优化四面体网格.在均匀网格的基础上,研究了自适应网格生成算法,在保持网格几何精度的同时精简单元数量,以提高有限元计算效率.给出了从CT数据生成人体股骨远端四面体网格的实例,该网格模型被用于虚拟膝关节镜手术.     

医学体数据中基于局部特征尺寸的Delaunay四面体化算法*

为了从医学体数据构建面向虚拟手术仿真系统的器官实体模型,提出一种基于局部特征尺寸的Delaunay四面体化算法。首先采用Marching Cubes算法和外存模型简化技术从体数据中得到器官等值面简化模型,提出重心射线法去除内部冗余网格,获得器官多面体表面;然后基于局部特征尺寸构建表面顶点保护球,结合Delaunay细分算法生成边界一致的初始四面体网格;最后提出基于随机扰动的空间分解法快速生成内部节点,并逐点插入到四面体网格中优化单元质量。该算法克服了Delaunay细分算法无法处理锐角输入的缺点,并从理论     

基于分类体数据的四面体网格剖分算法

虚拟内窥手术是以真实病人的CT或者MRI扫描数据为基础，首先通过组织分割，在计算机内部建立起三维模型，然后通过虚拟现实技术来模拟窥镜手术全过程的一项技术。其中，人体器官的三维网格建模是该技术中一个十分重要的部分，为了准确地进行了人体器官三维网格建模，在对三维体数据进行组织分割的基础上，提出了一种由分类体数据直接建立三维四面体网格的方法，由于Delaunay三角剖分所产生的网格质量比较高，所以该方法沿用逐点插入算法的思想，以特征点的提取和Steiner布点为基础来生成四面体网格，并通过组织边界的判定准则和利用flip操作来恢复组织边界，实践证明，该方法所生成的网格具有自适应的网格密度。     

面向四面体网格生成的Delaunay refinement器官表面重建

为满足生物医学仿真系统对器官几何模型在Delaunay表面重构和四面体建模两方面的需求,提出一种面向四面体网格生成的Delaunay refinement表面重构算法.算法将从医学体数据中经过等值面提取和简化的初始表面作为输入和边界限定条件,为每个限定点计算局部特征尺寸并构建保护球,计算保护球与限定线段的交点并与限定点一起作为初始点集,生成Delaunay辅助四面体网格,引入一个迭代细分过程恢复边界,最终获得Delaunay重构表面.针对细分过程中的收敛性问题,文中给出了详细的理论证明和算法实例.此外,通过Delaunay四面体生成的对比实验表明该算法在Delaunay器官表面重构和四面体建模两方面兼具有效性和优越性.     

高性能非结构化四面体网格解耦并行生成算法

针对大规模科学计算领域非结构化网格生成问题,提出一种基于AFT-Delaunay方法的三维复杂域解耦并行四面体网格生成算法.该算法以待剖分三维域的闭合的表面三角形网格为输入,采用边界一致约束Delaunay剖分方法串行地生成较小规模的初始四面体网格;采用界面优先策略扩展三维AFT-Delaunay方法,以几何分界面为参考指引前沿推进方向,在分界面处生成一层由四面体单元构成的有厚度的"墙",递归、并行地将初始四面体网格分割成完全解耦的子区域;此时,各子区域均为不含内部节点的四面体网格,继续利用AFT-Delaunay方法解耦并行地生成各子区域内部四面体网格.算例结果表明,文中算法很好地解决了分界面处网格质量差的难题以及收敛性问题,具有较好的并行效率及几何适应性,可在PC平台全自动地完成108量级的非结构四面体网格生成.     

基于Netgen的层状地质体四面体网格划分方法

为解决三维地质建模中难以表达层状地质体内部属性的问题,将有限元网格划分方法应用于层状地质体建模中,研究基于Netgen进行层状地质体四面体网格划分的方法.以地质钻探数据为数据源,按照钻孔数据分层构建三维表面模型,用三角面片的集合构成封闭的包围壳来描述层状地质体的外部形状;结合Netgen强大的几何自适应和细部划分控制功能,用四面体网格划分方法对形成的三维表面模型进行空间区域划分,从而实现对复杂形状的层状地质体三维模型构建,并分析Netgen的输入、输出数据结构和地质钻探数据到STL格式的三维模型数据、STL格式数据到Netgen网格划分结果数据的生成过程.某矿区多个岩层的模型构建证明该方法稳定、可靠且有效.     

德洛内三角剖分算法在三维医学图像方面的应用

本文提出一种新颖的适用于实时有限元分析的四面体网格生成算法，该算法在并行插入与删除网格节点的前提下，能够保证网络生成的质量即保证最小二面角的临界值和网格生成的保真度即能够保证组织的外部边界和组织间的边界。实验证明我们的算法适用于真实的医学图像，并且具有较好的加速比。     

三维并行约束Delaunay网格生成算法及实现

针对二维并行约束Delaunay网格生成算法直接应用于三维条件下会导致人工边界产生过短边的问题,提出并实现了基于主从模式的三维并行约束Delaunay网格生成算法.首先对求解区域进行分解,通过交换人工边界面上的数据解决子区域间网格一致性问题;其次为每个人工边界面选定主从子区域,由主子区域产生边界面网格并发送,从子区域负责接收;最后采用贪心算法平衡各个子区域的通信负载,得到算法效率的提升.实验结果表明,该算法可以大规模并行生成边界一致四面体网格,具有较好的并行效率,并能够保证最终的网格质量.     

Comparison of the meccano method with standard mesh generation techniques

The meccano method is a novel and promising mesh generation technique for simultaneously creating adaptive tetrahedral meshes and volume parameterizations of a complex solid. The method combines several former procedures: a mapping from the meccano boundary to the solid surface, a 3-D local refinement algorithm and a simultaneous mesh untangling and smoothing. In this paper we present the main advantages of our method against other standard mesh generation techniques. We show that our method constructs meshes that can be locally refined using the Kossaczky bisection rule and maintaining a high mesh quality. Finally, we generate volume T-mesh for isogeometric analysis, based on the volume parameterization obtained by the method.     

3D finite element meshing from imaging data

This paper describes an algorithm to extract adaptive and quality 3D meshes directly from volumetric imaging data. The extracted tetrahedral and hexahedral meshes are extensively used in the finite element method (FEM). A top-down octree subdivision coupled with a dual contouring method is used to rapidly extract adaptive 3D finite element meshes with correct topology from volumetric imaging data. The edge contraction and smoothing methods are used to improve mesh quality. The main contribution is extending the dual contouring method to crack-free interval volume 3D meshing with boundary feature sensitive adaptation. Compared to other tetrahedral extraction methods from imaging data, our method generates adaptive and quality 3D meshes without introducing any hanging nodes. The algorithm has been successfully applied to constructing quality meshes for finite element calculations.     

Feature-Sensitive Tetrahedral Mesh Generation with Guaranteed Quality

Tetrahedral meshes are being extensively used in finite element methods (FEM). This paper proposes an algorithm to generate feature-sensitive and high-quality tetrahedral meshes from an arbitrary surface mesh model. A top-down octree subdivision is conducted on the surface mesh and a set of tetrahedra are constructed using adaptive body-centered cubic (BCC) lattices. Special treatments are given to the tetrahedra near the surface such that the quality of the resulting tetrahedral mesh is provably guaranteed: the smallest dihedral angle is always greater than 5.71°. The meshes generated by our method are not only adaptive from the interior to the boundary, but also feature-sensitive on the surface with denser elements in high-curvature regions where geometric feature most likely reside. A variety of experimental results are presented to demonstrate the effectiveness and robustness of this algorithm.     

Adaptive Skin Meshes Coarsening for Biomolecular Simulation

In this paper, we present efficient algorithms for generating hierarchical molecular skin meshes with decreasing size and guaranteed quality. Our algorithms generate a sequence of coarse meshes for both the surfaces and the bounded volumes. Each coarser surface mesh is adaptive to the surface curvature and maintains the topology of the skin surface with guaranteed mesh quality. The corresponding tetrahedral mesh is conforming to the interface surface mesh and contains high quality tetrahedra that decompose both the interior of the molecule and the surrounding region (enclosed in a sphere). Our hierarchical tetrahedral meshes have a number of advantages that will facilitate fast and accurate multigrid PDE solvers. Firstly, the quality of both the surface triangulations and tetrahedral meshes is guaranteed. Secondly, the interface in the tetrahedral mesh is an accurate approximation of the molecular boundary. In particular, all the boundary points lie on the skin surface. Thirdly, our meshes are Delaunay meshes. Finally, the meshes are adaptive to the geometry.     

Template-based finite-element mesh generation from medical images

The finite-element (FE) method is commonly used in biomedical engineering to simulate the behaviour of biological structures because of its ability to model complex shapes in a subject-specific manner. However, generating FE meshes from medical images remains a bottleneck. We present a template-based technique for semi-automatically generating FE meshes which is applicable to prospective studies of individual patients in which FE meshes must be generated from scans of the same structure taken at different points in time to study the effects of disease progression/regression. In this "template-based" meshing approach, the baseline FE (tetrahedral) volume mesh is first manually aligned with the follow-up images. The triangulated surface of the mesh is then automatically deformed to fit the imaged organ boundary. The deformed surface nodes are then smoothed using a Laplacian smoothing algorithm to correct triangle (surface nodes) distortion and thus preserve triangle quality. Finally, the internal mesh nodes are smoothed to correct distorted tetrahedral elements and thus preserve tetrahedral element quality. This template-based approach is shown to be as accurate and precise as the previous technique used by our group, while preserving element quality and volume.     

A sharpness-dependent filter for recovering sharp features in repaired 3D mesh models

This paper presents a sharpness-based method for hole-filling that can repair a 3D model such that its shape conforms to that of the original model. The method involves two processes: interpolation-based hole-filling, which produces an initial repaired model; and post-processing, which adjusts the shape of the initial repaired model to conform to that of the original model. In the interpolation-based hole-filling process, a surface interpolation algorithm based on the radial basis function creates a smooth implicit surface that fills the hole. Then, a regularized marching tetrahedral algorithm is used to triangulate the implicit surface. Finally a stitching and regulating strategy is applied to the surface patch and its neighboring boundary polygon meshes to produce an initial repaired mesh model, which is a regular mesh model suitable for post-processing. During post-processing, a sharpness dependent filtering algorithm is applied to the initial repaired model. This is an iterative procedure whereby each iteration step adjusts the face normal associated with each meshed polygon to recover the sharp features hidden in the repaired model. The experiment results demonstrate that the method is effective in repairing incomplete 3D mesh models.     

Adaptive-size meshes for rigid and nonrigid shape analysis andsynthesis

A physically based modeling method that uses adaptive-size meshes to model surfaces of rigid and nonrigid objects is presented. The initial model uses an a priori determined mesh size. However, the mesh size increases or decreases dynamically during surface reconstruction to locate nodes near surface areas of interest (like high curvature points) and to optimize the fitting error. Further, presented with multiple 3-D data frames, the mesh size varies as the data surface undergoes nonrigid motion. This model is used to reconstruct 3-D surfaces, analyze the nonrigid motion, track the corresponding points in nonrigid motion, and create graphic animation and visualization. The method was tested on real range data, on simulated nonrigid motion, and on real data for the left ventricular motion