Geometrically deformed models: a method for extracting closed geometric models form volume data
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Semi-automatic generation of transfer functions for direct volume rendering
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Surfels: surface elements as rendering primitives
Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Image segmentation by fuzzy clustering: methods and issues
Handbook of medical imaging
Handbook of medical imaging
Shape constraints in deformable models
Handbook of medical imaging
Gradient vector flow deformable models
Handbook of medical imaging
Handbook of medical imaging
Interpolation and Approximation of Surfaces from Three-dimensional Scattered Data Points
Dagstuhl '97, Scientific Visualization
Anti-Aliased volume extraction
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
Resolution Independent Deformable Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Visualizing Industrial CT Volume Data for Nondestructive Testing Applications
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
A topology preserving level set method for geometric deformable models
IEEE Transactions on Pattern Analysis and Machine Intelligence
The power crust, unions of balls, and the medial axis transform
Computational Geometry: Theory and Applications
LiveSync++: enhancements of an interaction metaphor
GI '08 Proceedings of graphics interface 2008
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In many volume segmentation and visualization tasks, the ability to correctly identify the boundary surface of each volumetric feature of interest in the data is desirable. This surface can be used in subsequent quantitative studies of the segmented features. In this paper, we present an automatic approach to generate accurate representations of a feature of interest from volume segmentation. Our method first locates a set of points, which tightly define the boundary of the volumetric feature. This set of points can then be used to construct a boundary surface mesh. We also describe how to construct an anti-aliased volume representation of the segmented feature from this point set to enable high-quality volume rendering of the feature. These three representations - point set, boundary surface mesh, and anti-aliased volume segment - have a wide variety of applications.