Mesh generation from imaging data

Handbook of Computational Geometry, 2000

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.

Effective Computational Geometry for Curves and Surfaces, 2006

2007

Abstract: This paper describes an approach to construct unstructured tetrahedral and hexa-hedral meshes for a domain with multiple materials. We have developed an octree-based iso-contouring method to construct unstructured 3D meshes for a single material domain. Based on it, we analyze each material change edge instead of sign change edge to figure out in-terfaces between two materials, and mesh each material region with conforming boundaries. Two kinds of surfaces, the boundary surface and the interface between two different material regions, are meshed and distinguished. Both material change edges and interior edges are an-alyzed to construct tetrahedral meshes, and interior grid points are analyzed for hexahedral mesh construction. Finally the edge-contraction and smoothing method is used to improve the quality of tetrahedral meshes, and a combination of pillowing, geometric flow and optimiza-tion techniques are used for hexahedral mesh quality improvement. The shrink set is def...

2000

A novel algorithm to extrude smooth, near-body volume meshes from surface meshes of arbitrary topology is presented. These meshes are classified as generalized meshes because multiple element topologies may be present within the same mesh. The algorithm utilizes a three-step, parabolic scheme based on the Poisson equation used in structured grid generation to extrude the volume mesh. Several preliminary example meshes are included to demonstrate the efficacy of the approach.

The Visual Computer, 2011

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a ...

Lecture Notes in Computer Science, 2009

The problem of generating realistic computer models of objects represented by 3D segmented images is important in many biomedical applications. Labelled 3D images impose particular challenges for meshing algorithms because multi-material junctions form features such as surface pacthes, edges and corners which need to be preserved into the output mesh. In this paper, we propose a feature preserving Delaunay refinement algorithm which can be used to generate high-quality tetrahedral meshes from segmented images. The idea is to explicitly sample corners and edges from the input image and to constrain the Delaunay refinement algorithm to preserve these features in addition to the surface patches. Our experimental results on segmented medical images have shown that, within a few seconds, the algorithm outputs a tetrahedral mesh in which each material is represented as a consistent submesh without gaps and overlaps. The optimization property of the Delaunay triangulation makes these meshes suitable for the purpose of realistic visualization or finite element simulations.

Advances in Engineering Software (1978), 1979

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Comptes Rendus de l'Académie des Sciences - Series IIB - Mechanics, 2000

Many physical phenomena in science and engineering can be modeled by partial differential equations (PDEs) and solved by means of the Finite Element Method (FEM). Such a method uses as computational spatial support a mesh of the domain where the equations are formulated. Mesh quality is a key-point for the accuracy of numerical simulation. In this paper, we are concerned with the generation of quality (or regular) meshes. This question is a particular occurrence of a more general mesh generation issue which aims to complete meshes conforming to a pre-specified size map (such meshes being referred to as 'unit' meshes). We propose a method that makes this mesh construction possible. It is based on a Delaunay advancing-front combined method: the field points are defined using an advancing-front method and are connected using a generalized Delaunay type method. Some optimization methods are also discussed. © 2000 Académie des sciences/Éditions scientifiques et médicales Elsevier SAS quality meshes / adaptive meshing / anisotropic meshes / surface meshing

2008

The paper presents MeshLab, an open source, extensible, mesh processing system that has been developed at the Visual Computing Lab of the ISTI-CNR with the helps of tens of students. We will describe the MeshLab architecture, its main features and design objectives discussing what strategies have been used to support its development. Various examples of the practical uses of MeshLab in research and professional frameworks are reported to show the various capabilities of the presented system.

International Journal For Numerical Methods in Biomedical Engineering, 2012

An overview of surface and volume mesh generation techniques for creating valid meshes to carry out biomedical flows is provided. The methods presented are designed for robust numerical modelling of biofluid flow through subject-specific geometries. The applications of interest are haemodynamics in blood vessels and air flow in upper human respiratory tract. The methods described are designed to minimize distortion to a given domain boundary. They are also designed to generate a triangular surface mesh first and then volume mesh (tetrahedrons) with high quality surface and volume elements. For blood flow applications, a simple procedure to generate a boundary layer mesh is also described. The methods described here are semiautomatic in nature because of the fact that the geometries are complex, and automation of the procedures may be possible if high quality scans are used. of a well-defined object and patient-specific geometry is in building the surface mesh. Because the surface is not analytically defined in subject-specific applications, alternative approaches to that of the standard geometries are required.

2002

Figure 1: A series of adaptive tetrahedral meshes with different error tolerance are extracted from UNC Head (CT). Isovalues α in = 1000.0, α out = 120.0; error tolerance ε in = 0.0001, (ε out , the number of elements) = leftmost: (0.

First and foremost, I would like to express my sincere appreciation and gratitude to my supervisor, Associate Professor Cai Jianfei, for his persistent support and invaluable advice in my research and preparation of this report. It has been a great pleasure to have him as my supervisor. I would also like to express my gratitude to Associate Professor Zheng Jianmin, for his invaluable guidance, advice, and comments to my research. Finally, I would like to express my appreciation to my fellow graduate students in the Center for Multimedia and Network Technology for the helpful discussions.

2011

To provide simulation software in the field of TCAD with the utmost flexibility regarding generation and adaptation of meshes, a generic and high-quality meshing library, ViennaMesh, has been developed. The library is coded in C++ and utilizes modern programming techniques to wrap tasks, like mesh generation and mesh adaptation, into functional objects, which can then be concatenated to form the desired meshing process. Additionally, a meta-selection environment provides the ability to select a mesh generation kernel based on properties already defined at compile time. Code examples are depicted and briefly discussed. Moreover, several enhancements to existing mesh adaptation methods have been made, which are demonstrated based on meshes provided by industrial partners.

Abstract. Techniques devoted to generate a triangular mesh from images either take as starting point a segmented image or generate a mesh without distinguishing different structures contained in the image. The need for pre-segmentation and the absence of well defined structures may rule out the use of the resulting mesh in some applications, as numerical simulations.