Strategy of statistics-based visualization for segmented 3d cardiac volume data set

Authors:
Changqing Gai;Kuanquan Wang;Lei Zhang;Wangmeng Zuo
Affiliations:
Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China;Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Year:
2011

Citing 7
Cited 0

Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets

Proceedings of the conference on Visualization '01
Multidimensional Transfer Functions for Interactive Volume Rendering

IEEE Transactions on Visualization and Computer Graphics
A single-pass GPU ray casting framework for interactive out-of-core rendering of massive volumetric datasets

The Visual Computer: International Journal of Computer Graphics
Multimodal volume rendering with 3D textures

Computers and Graphics
Dynamic Shader Generation for GPU-Based Multi-Volume Ray Casting

IEEE Computer Graphics and Applications
Sinus Endoscopy - Application of Advanced GPU Volume Rendering for Virtual Endoscopy

IEEE Transactions on Visualization and Computer Graphics
Structuring Feature Space: A Non-Parametric Method for Volumetric Transfer Function Generation

IEEE Transactions on Visualization and Computer Graphics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a method to design the transfer function of segmented cardiac volume data set by using statistical information of the cardiac tissues. To explore the interior subtle tissues of heart, visualization strategy is provided to guide the user to a satisfied rendering result with the help of opacity and gradient magnitude modulation. Using the visible human cardiac data set segmented from the CT data, experimental results indicate that our method can provide high quality rendering result and multi-level visualization effect.