20 May 1999 Volume segmentation and rendering of mixtures of materials for virtual colonoscopy
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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.
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Rui C. H. Chiou, Rui C. H. Chiou, Dongqing Chen, Dongqing Chen, Zhengrong Liang, Zhengrong Liang, Arie E. Kaufman, Arie E. Kaufman, "Volume segmentation and rendering of mixtures of materials for virtual colonoscopy", Proc. SPIE 3660, Medical Imaging 1999: Physiology and Function from Multidimensional Images, (20 May 1999); doi: 10.1117/12.349582; https://doi.org/10.1117/12.349582
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