Size-based transfer functions : a new volume exploration technique

The visualization of complex 3D images remains a challenge, a fact that is magnified by the difficulty to classify or segment volume data. In this paper, we introduce size-based transfer functions, which map the local scale of features to color and opacity. Features in a data set with similar or ide...

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Détails bibliographiques
Publié dans:IEEE transactions on visualization and computer graphics. - 1996. - 14(2008), 6 vom: Nov., Seite 1380-7
Auteur principal: Correa, Carlos D (Auteur)
Autres auteurs: Ma, Kwan-Liu
Format: Article en ligne
Langue:English
Publié: 2008
Accès à la collection:IEEE transactions on visualization and computer graphics
Sujets:Journal Article Research Support, U.S. Gov't, Non-P.H.S.
Description
Résumé:The visualization of complex 3D images remains a challenge, a fact that is magnified by the difficulty to classify or segment volume data. In this paper, we introduce size-based transfer functions, which map the local scale of features to color and opacity. Features in a data set with similar or identical scalar values can be classified based on their relative size. We achieve this with the use of scale fields, which are 3D fields that represent the relative size of the local feature at each voxel. We present a mechanism for obtaining these scale fields at interactive rates, through a continuous scale-space analysis and a set of detection filters. Through a number of examples, we show that size-based transfer functions can improve classification and enhance volume rendering techniques, such as maximum intensity projection. The ability to classify objects based on local size at interactive rates proves to be a powerful method for complex data exploration
Description:Date Completed 30.12.2008
Date Revised 07.11.2008
published: Print
Citation Status MEDLINE
ISSN:1941-0506
DOI:10.1109/TVCG.2008.162