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MIP-Guided Vascular Image Visualization with Multi-Dimensional Transfer Function

Teacher Information

Name
WU Yingcai ZJU Faculty Homepage
Department
INTL Campus
Research
Visual Analytics, Information Visualization, Human Computer Interaction
Document Type
Book Chapter
Advances in Computer Graphics

Publication

Chapter Title
MIP-Guided Vascular Image Visualization with Multi-Dimensional Transfer Function
Author
Ming-Yuen Chan, Yingcai Wu, Huamin Qu, Albert C. S. Chung & Wilbur C. K. Wong
Page
372–384
Source Title
Advances in Computer Graphics
Subtitle
24th Computer Graphics International Conference, CGI 2006, Hangzhou, China, June 26-28, 2006, Proceedings
Author/Author of Source
Tomoyuki Nishita, Qunsheng Peng, Hans-Peter Seidel
Publisher
Springer
P-ISBN
978-3-540-35638-7
E-ISBN
9783540356394
Abstract

Direct volume rendering (DVR) is an effective way to visualize 3D vascular images for diagnosis of different vascular pathologies and planning of surgical treatments. Angiograms are typically noisy, fuzzy, and contain thin vessel structures. Therefore, some kinds of enhancements are usually needed before direct volume rendering can start. However, without visualizing the 3D structures in angiograms, users may find it difficult to select appropriate parameters and assess the effectiveness of the enhancement results. In addition, traditional enhancement techniques cannot easily separate the vessel voxels from other contextual structures with the same or very similar intensity. In this paper, we propose a framework to integrate enhancement and direct volume rendering into one visualization pipeline using multi-dimensional transfer function tailored for visualizing the curvilinear and line structures in angiograms. Furthermore, we present a feature preserving interpolation method to render very thin vessels which are usually missed using traditional approaches. To ease the difficulty in vessel selection, a MIP-guided method is suggested to assist the process.

DOI
https://doi.org/10.1007/11784203_32

Print & Electronic Holdings

Database
Springer
Link