Automated Structured All-Quadrilateral and Hexahedral Meshing of Tubular Surfaces

Xiong, Guanglei; Musuvathy, Suraj; Fang, Tong

doi:10.1007/978-3-642-33573-0_7

Cited by 3 publications

(6 citation statements)

References 19 publications

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“…For instance, tubular structures appears in many industrial and medical applications. In references [81,82] two different strategies for this kind of geometries are presented.…”

Section: Other Methodsmentioning

confidence: 99%

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

Ramos¹,

Ruiz‐Gironés²,

Navarro³

2014

Comp. Tech. Rev.

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Discretization techniques such the finite element method, the finite volume method or the discontinuous Galerkin method are the most used simulation techniques in applied sciences and technology. These methods rely on a spatial discretization adapted to the geometry and to the prescribed distribution of element size. Several fast and robust algorithms have been developed to generate triangular and tetrahedral meshes. In these methods local connectivity modifications are a crucial step. Nevertheless, in hexahedral meshes the connectivity modifications propagate through the mesh. In this sense, hexahedral meshes are more constrained and therefore, more difficult to generate. However, in many applications such as boundary layers in computational fluid dynamics or composite material in structural analysis hexahedral meshes are preferred. In this work we present a survey of developed methods for generating structured and unstructured hexahedral meshes.

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“…For instance, tubular structures appears in many industrial and medical applications. In references [81,82] two different strategies for this kind of geometries are presented.…”

Section: Other Methodsmentioning

confidence: 99%

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

Ramos¹,

Ruiz‐Gironés²,

Navarro³

2014

Comp. Tech. Rev.

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“…Indeed, only 49% of the cells have a scaled Jacobian above 0.9 in average on the distributions given for three large cerebral networks in [13]. This proportion goes up to 62% of the cells of the abdominal aortic artery geometry meshed by the method of [41]. Finally, in [9], between 65% and 82% -depending on the case and the cell density -of the cells of the aortic arch meshed have a scaled Jacobian value between 0.8 and 1.…”

Section: Mesh Qualitymentioning

confidence: 98%

“…De Santis et al introduced semi-automatic methods, ranging from manual selection of the most relevant slices of the input surface mesh [10], user defined bifurcation coordinate system [8], to the generation and adjustment of a block-structure representation of the network [9]. Automatic methods are based on Voronoi diagram [4], resolution of the Laplace's equation [37], random-walk algorithm [41] or branching templates [43] or parametric models [13]. The hexahedral meshing can then be created from the decomposition through various techniques ; Copper scheme in the work of [4], template grid sweeping for [37], [43] and [13], Bezier spline modeling followed by an iso-parametric transformation of a template mesh [8], projection and refinement of block-structures [9], Laplacian-based harmonic functions combined with Catmull-Clark subdivision [41].…”

Section: Related Work 21 Hexahedral Meshingmentioning

confidence: 99%

Modeling and hexahedral meshing of arterial networks from centerlines

Decroocq¹,

Frindel²,

Ohta³

et al. 2022

Preprint

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Computational fluid dynamics (CFD) simulation provides valuable information on blood flow from the vascular geometry. However, it requires to extract accurate models of arteries from low resolution medical images, which remains challenging. Centerline-based representation is widely used to model large vascular networks with small vessels, as it enables manual editing and encodes the topological information. In this work, we propose an automatic method to generate an hexahedral mesh suitable for CFD directly from centerlines. The proposed method is an improvement of the state-of-the-art in terms of robustness, mesh quality and reproductibility.Both the modeling and meshing tasks are addressed. A new vessel model based on penalized splines is proposed to overcome the limitations inherent to the centerline representation, such as noise and sparsity. Bifurcations are reconstructed using a physiologically accurate parametric model that we extended to planar n-furcations. Finally, a volume mesh with structured, hexahedral and flow oriented cells is produced from the proposed vascular network model.The proposed method offers a better robustness and mesh quality than the state-of-the-art methods. As it combines both modeling and meshing techniques, it can be applied to edit the geometry and topology of vascular models effortlessly to study the impact on hemodynamics. We demonstrate the efficiency of our method by entirely meshing a dataset of 60 cerebral vascular networks. 92% of the vessels and 83% of the bifurcations where mesh without defects needing manual intervention, despite the challenging aspect of the input data. The source code will be released publicly.

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“…However, most implementations require manual intervention when applied for vascular trees. Some procedures require a smoothed surface mesh for hexahedral volumetric mesh generation 23,24 , but it is extremely laborious to manually obtain a high quality surface mesh with no gaps and discontinuity from medical images for a large-scale cerebral arterial tree. Size and complex connectivity of cerebral arterial trees with hundreds of bifurcations and branches call for automated image segmentation and mesh processing.…”

Section: Introductionmentioning

confidence: 99%

“…For example, some methods are limited to planar bifurcations 10,15,24,25 (bifurcation branches lying in a single plane), however, non-planar bifurcations are prevalent in the human vascular trees 26 . Other procedures fail in short segments between bifurcations 23 or segments with high tortuosity 27 .…”

Section: Introductionmentioning

confidence: 99%

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation

Ghaffari

Tangen

Alaraj

et al. 2017

Computers in Biology and Medicine

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In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications.

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Automated Structured All-Quadrilateral and Hexahedral Meshing of Tubular Surfaces

Cited by 3 publications

References 19 publications

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

Unstructured and Semi-Structured Hexahedral Mesh Generation Methods

Modeling and hexahedral meshing of arterial networks from centerlines

Large-scale subject-specific cerebral arterial tree modeling using automated parametric mesh generation for blood flow simulation

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