Volumetric data exploration using interval volume

Fujishiro, Issei; Maeda, Yuji; Sato, Hiroshi; Takeshima, Yuriko

doi:10.1109/2945.506226

Cited by 47 publications

(28 citation statements)

References 22 publications

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“…MC was extended to extract tetrahedral meshes between two isosurfaces [17]. A different and systematic algorithm was proposed for interval volume tetrahedralization [34].…”

Section: Mesh Generationmentioning

confidence: 99%

Quality meshing of implicit solvation models of biomolecular structures

Zhang

Bajaj

2006

Computer Aided Geometric Design

104

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This paper describes a comprehensive approach to construct quality meshes for implicit solvation models of biomolecular structures starting from atomic resolution data in the Protein Data Bank (PDB). First, a smooth volumetric electron density map is constructed from atomic data using weighted Gaussian isotropic kernel functions and a two-level clustering technique. This enables the selection of a smooth implicit solvation surface approximation to the Lee-Richards molecular surface. Next, a modified dual contouring method is used to extract triangular meshes for the surface, and tetrahedral meshes for the volume inside or outside the molecule within a bounding sphere/box of influence. Finally, geometric flow techniques are used to improve the surface and volume mesh quality. Several examples are presented, including generated meshes for biomolecules that have been successfully used in finite element simulations involving solvation energetics and binding rate constants.

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“…MC was extended to extract tetrahedral meshes between two isosurfaces [17]. A different and systematic algorithm was proposed for interval volume tetrahedralization [34].…”

Section: Mesh Generationmentioning

confidence: 99%

Quality meshing of implicit solvation models of biomolecular structures

Zhang

Bajaj

2006

Computer Aided Geometric Design

104

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“…MC was extended to extract tetrahedral meshes between two isosurfaces directly from volume data [24]. A Branch-on-Need octree was used as an auxiliary data structure to accelerate the extraction process.…”

Section: Tetrahedral Mesh Generationmentioning

confidence: 99%

3D finite element meshing from imaging data

Zhang

Bajaj

Sohn

2005

Computer Methods in Applied Mechanics and Engineering

165

134

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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 the 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 the mesh quality. The main contribution is extending the dual contouring method to crack-free interval volume 3D meshing with 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 the geometric model of a biomolecule in finite element calculations.

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“…3.3). While prior work uses, e.g., interval volumes [7], to derive measures such as area and volume for contours (i.e., connected isosurface components), our approach provides these measures as a function of isovalue that is associated with contour tree edges. This function representation makes it possible to compute an individual, contour-specific area or volume for any isovalue along an edge, as opposed to approximating a single volume for an entire edge like prior work on topology simplification [20,21].…”

Section: Computing Per-component Measuresmentioning

confidence: 99%

Topological Cacti: Visualizing Contour-Based Statistics

Weber

Bremer

Pascucci

2011

Mathematics and Visualization

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Contours, the connected components of level sets, play an important role in understanding the global structure of a scalar field. In particular their nesting behavior and topology-often represented in form of a contour tree-have been used extensively for visualization and analysis. However, traditional contour trees only encode structural properties like number of contours or the nesting of contours, but little quantitative information such as volume or other statistics. Here we use the segmentation implied by a contour tree to compute a large number of per-contour (interval) based statistics of both the function defining the contour tree as well as other co-located functions. We introduce a new visual metaphor for contour trees, called topological cacti, that extends the traditional toporrery display of a contour tree to display additional quantitative information as width of the cactus trunk and length of its spikes. We apply the new technique to scalar fields of varying dimension and different measures to demonstrate the effectiveness of the approach.

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Volumetric data exploration using interval volume

Cited by 47 publications

References 22 publications

Quality meshing of implicit solvation models of biomolecular structures

Quality meshing of implicit solvation models of biomolecular structures

3D finite element meshing from imaging data

Topological Cacti: Visualizing Contour-Based Statistics

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