ArticleComputer aided design2012
Feature-Sensitive Tetrahedral Mesh Generation with Guaranteed Quality.
Article in Computer aided design, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model.Scientific reports · 2023Article
- Computed Tomography-Based Preoperative Simulation System for Pedicle Screw Fixation in Spinal Surgery.Journal of Korean medical science · 2020Article
- Lumbar model generator: a tool for the automated generation of a parametric scalable model of the lumbar spine.Journal of the Royal Society, Interface · 2018Article
- A novel cortical thickness estimation method based on volumetric Laplace-Beltrami operator and heat kernel.Medical image analysis · 2015Article
- Lattice cleaving: a multimaterial tetrahedral meshing algorithm with guarantees.IEEE transactions on visualization and computer graphics · 2014Article
- New software developments for quality mesh generation and optimization from biomedical imaging data.Computer methods and programs in biomedicine · 2014Article
- Free Tools and Strategies for the Generation of 3D Finite Element Meshes: Modeling of the Cardiac Structures.International journal of biomedical imaging · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
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.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.