Volume Refinement Fairing Isosurfaces
VIS '04 Proceedings of the conference on Visualization '04
Fairing Scalar Fields by Variational Modeling of Contours
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Topology-Controlled Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Topology correction of segmented medical images using a fast marching algorithm
Computer Methods and Programs in Biomedicine
Topological Landscapes: A Terrain Metaphor for Scientific Data
IEEE Transactions on Visualization and Computer Graphics
Describing shapes by geometrical-topological properties of real functions
ACM Computing Surveys (CSUR)
Detecting critical regions in multidimensional data sets
Computers & Mathematics with Applications
Topology correction using fast marching methods and its application to brain segmentation
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Topology preserving tissue classification with fast marching and topology templates
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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Trivariate data is commonly visualized using isosurfaces or direct volume rendering. When exploring scalar fields by isosurface extraction it is often difficult to choose isovalues that convey "useful" information. The significance of visualizations using direct volume rendering depends on the choice of good transfer functions. Understanding and using isosurface topology can help in identifying "relevant" isovalues for visualization via isosurfaces and can be used to automatically generate transfer functions.Critical isovalues indicate changes in topology of an isosurface: the creation of new surface components, merging of surface components or the formation of holes in a surface component. Interesting isosurface behavior is likely to occur at and around critical isovalues. Current approaches to detect critical isovalues are usually limited to isolated critical points. Data sets often contain regions of constant value (i.e., mesh edges, mesh faces, or entire mesh cells). We present a method that detects critical points, critical regions and corresponding critical isovalues for a scalar field defined by piecewise trilinear interpolation over a uniform rectilinear grid. We describe how to use the resulting list of critical regions/points and associated values to examine trivariate data.