Comparing Techniques for Tetrahedral Mesh Generation (original) (raw)
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Semi-automatic surface and volume mesh generation for subject-specific biomedical geometries
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.
Tetrahedral mesh generation for medical images with multiple regions using active surfaces
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010
In this paper, we present a method for automatically generating tetrahedral meshes from 3D images with multiple region labels. The first step consists of constructing an adaptively sized tetrahedral mesh that conforms exactly to the voxelized regions in the image. Active surfaces (active contours in 2D) are then employed to smooth the region boundaries and remove the voxelization. Specifically, an energy with three terms is minimized: a smoothing term to remove the voxelization, a fidelity term to keep the mesh from moving too far away from the image data, and an elasticity term to keep the tetrahedra from becoming flattened or inverted as the mesh deforms. The algorithm for tetrahedral mesh generation is applied to an MRI image that has been automatically segmented using an existing method. The resulting mesh has a number of desirable properties such as tetrahedra with all dihedral angles away from 0 and 180 degrees, smoothness, and a high level of detail for the number of tetrahedra used.
Tetrahedral Mesh Generation for Medical Imaging
Medical Image Computing and Computer-Assisted Intervention, 2000
We describe the open source implementation of an adap- tive tetrahedral mesh generator particularly targeted for non-rigid FEM registration of MR images. While many medical imaging applications re- quire robust mesh generation, there are few codes available. Moreover, most of the practical implementations are commercial. The algorithm we have implemented has been previously evaluated for simulations of highly deformable objects,
Generation and adaptation of computational surface meshes from discrete anatomical data
International Journal for Numerical Methods in Engineering, 2004
Fast and accurate scanning devices are nowadays widely used in many engineering and biomedical fields. The resulting discrete data is usually directly converted into polygonal surface meshes, using 'brute-force' algorithms, often resulting in meshes that may contain several millions of polygons. Simplification is therefore required in order to make storage, computation and display possible if not efficient. In this paper, we present a general scheme for mesh simplification and optimization that allows to control the geometric approximation as well as the element shape and size quality (required for numerical simulations). Several examples ranging from academic to complex biomedical geometries (organs) are presented to illustrate the efficiency and the utility of the proposed approach.
Tetrahedral Image-To-Mesh Conversion for Anatomical Modeling and Surgical Simulations
2015
We present an Image-To-Mesh Conversion method for building a realistic biomechanical model particularly targeted for surgical simulations. Our implementation generates tetrahedral meshes that conform to the physical boundaries of multilabel segmented images. Our approach, initially creates a Body-Centered Cubic (BCC) lattice that is a coarse approximation of the object boundaries, and then subdivides the lattice using a red-green refinement strategy that guarantees the high quality of the new elements. In a later step, our method deforms the lattice surfaces to their corresponding tissue boundaries using a point-based registration scheme. As a result, the final mesh is smooth and accurately represents the object boundaries allowing a faithful response of the biomechanical properties of the tissues involved in a surgical simulation. Besides, the generated mesh is adaptive with smaller elements in areas where more detail is desired and larger elements in the remainder of the image reg...
From medical images to computational meshes
Numerical simulations take a bigger importance in medical activity as they allow to obtain information non-invasively. To take into account individual variability, we propose numerical simulations in geometries reconstructed from medical images. We present the necessary treatment of images of diseased vessels, to provide a computational mesh of an anatomical model of the subject. First a faceted surface is extracted from the images. Then this surface is transformed into a geometrical model to be finally remeshed for a finite element use.
Generation of computational meshes from MRI and CT-scan data
2005
There are fields of engineering where accurate and personalised data are required; biomedical applications are one such example. We describe here a general purpose method to create computational meshes based on the analysis and segmentation of raw medical imaging data. The various ingredients are not new: a segmentation method based on deformable contours and a surface and volume mesh adaptation method based on discrete metric specifications; but the challenge that motivated this paper is to put them together in an attempt to design an automatic, easy to use and efficient 3D code.
International Journal for Numerical Methods in Biomedical Engineering, 2021
In order to simulate the cardiac function for a patient‐specific geometry, the generation of the computational mesh is crucially important. In practice, the input is typically a set of unprocessed polygonal surfaces coming either from a template geometry or from medical images. These surfaces need ad‐hoc processing to be suitable for a volumetric mesh generation. In this work we propose a set of new algorithms and tools aiming to facilitate the mesh generation process. In particular, we focus on different aspects of a cardiac mesh generation pipeline: (1) specific polygonal surface processing for cardiac geometries, like connection of different heart chambers or segmentation outputs; (2) generation of accurate boundary tags; (3) definition of mesh‐size functions dependent on relevant geometric quantities; (4) processing and connecting together several volumetric meshes. The new algorithms—implemented in the open‐source software vmtk—can be combined with each other allowing the creat...
A Medical Volume Reconstruction Method using Tetrahedral Meshes and Level Set
International Journal of Computer Assisted Radiology and Surgery
A volumetric medical image reconstruction method using tetrahedral meshes and level set is proposed whereby non-discrete models are reconstructed from grid based volume By this method, the discrete volumetric medical image is first segmented by coupled level sets driven by a pathologically modelled energy functional. The segmentation will divide the volume into pathologically meaningful regions. The volume will then be changed from regular grid data to a tetrahedral mesh. To reduce the volume of the mesh, a hybrid sculpting scheme is proposed to reduce the amount of redundancy and noise while preserving the important features. The hybrid sculpting scheme consists of internal sculpting and surface sculpting, which is able to provide multiple levels of detail through each iteration of sculpting thus enabling efficient reconstruction and visualization of the data. Initial results show that the proposed framework is able to maintain important features with reduced data volume while changing the data representation from regular grids to a tetrahedral mesh.
Construction of volume meshes from computed tomography data
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2005
In this paper, we present a new method, called marching volume elements (MVE), for automatically constructing a volume mesh from three-dimensional (3-D) high-resolution computed tomography (CT) data. The volume mesh generated by the MVE algorithm is suitable for computational fluid dynamics (CFD) simulations. The MVE algorithm is based on the marching cubes (MC) algorithm which is a surface generation algorithm for 3-D intensity data. The mesh created with the MVE algorithm is composed of pyramids, cubes and tetrahedrons with common faces that fit together to form a topologically consistent volume. We validate the MVE algorithm on a synthetic object and demonstrate it on CT scans of a human nasal cavity.