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Proceedings Paper

Volume segmentation and rendering of mixtures of materials for virtual colonoscopy
Author(s): Rui C. H. Chiou; Dongqing Chen; Zhengrong Liang; Arie E. Kaufman
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Paper Abstract

We focus on color mapping between gray tons of computed tomographic images and color texture of visible human or optical images. Particularly, we propose probabilistic segmentation based on gradient entropy and Bayesian estimation to solve the material mixture problems. The approach can fill in the gap between segmentation and rendering to eliminate artifacts (jagged edges) produced by incorrect classification of material mixture and to estimate accurate surface normal for volume shading.

Paper Details

Date Published: 20 May 1999
PDF: 6 pages
Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); doi: 10.1117/12.349582
Show Author Affiliations
Rui C. H. Chiou, SUNY/Stony Brook (United States)
Dongqing Chen, SUNY/Stony Brook (United States)
Zhengrong Liang, SUNY/Stony Brook (United States)
Arie E. Kaufman, SUNY/Stony Brook (United States)

Published in SPIE Proceedings Vol. 3660:
Medical Imaging 1999: Physiology and Function from Multidimensional Images
Chin-Tu Chen; Anne V. Clough, Editor(s)

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