Volume segmentation and rendering of mixtures of materials for virtual colonoscopy

Rui C.H. Chiou; Dongqing Chen; Zhengrong Liang; Arie E. Kaufman

Volume segmentation and rendering of mixtures of materials for virtual colonoscopy

Rui C.H. Chiou
, Dongqing Chen
, Zhengrong Liang
, Arie E. Kaufman

Stony Brook University

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English
Pages (from-to)	133-138
Number of pages	6
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3660
State	Published - 1999
Event	Proceedings of the 1999 Medical Imaging - Physiology and Function from Multidimensional Images - San Diego, CA, USA Duration: Feb 21 1999 → Feb 23 1999

Cite this

@article{ccb464e98f944ad19624e8ecdf8939e9,

title = "Volume segmentation and rendering of mixtures of materials for virtual colonoscopy",

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.",

author = "Chiou, \{Rui C.H.\} and Dongqing Chen and Zhengrong Liang and Kaufman, \{Arie E.\}",

year = "1999",

language = "English",

volume = "3660",

pages = "133--138",

journal = "Proceedings of SPIE - The International Society for Optical Engineering",

issn = "0277-786X",

note = "Proceedings of the 1999 Medical Imaging - Physiology and Function from Multidimensional Images ; Conference date: 21-02-1999 Through 23-02-1999",

}

TY - JOUR

T1 - Volume segmentation and rendering of mixtures of materials for virtual colonoscopy

AU - Chiou, Rui C.H.

AU - Chen, Dongqing

AU - Liang, Zhengrong

AU - Kaufman, Arie E.

PY - 1999

Y1 - 1999

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0032593704

M3 - Conference article

AN - SCOPUS:0032593704

SN - 0277-786X

VL - 3660

SP - 133

EP - 138

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Proceedings of the 1999 Medical Imaging - Physiology and Function from Multidimensional Images

Y2 - 21 February 1999 through 23 February 1999

ER -

Volume segmentation and rendering of mixtures of materials for virtual colonoscopy

Abstract

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