Skeleton cuts-An efficient segmentation method for volume rendering

Xiang, Dehui; Tian, Jie; Yang, Fei; Yang, Qi; Zhang, Xing; Li, Qingde; Liu, Xin

Abstract

Volume rendering has long been used as a key technique for volume data visualization, which works by using a transfer function to map color and opacity to each voxel. Many volume rendering approaches proposed so far for voxels classification have been limited in a single global transfer function, which is in general unable to properly visualize interested structures. In this paper, we propose a localized volume data visualization approach which regards volume visualization as a combination of two mutually related processes: the segmentation of interested structures and the visualization using a locally designed transfer function for each individual structure of interest. As shown in our work, a new interactive segmentation algorithm is advanced via skeletons to properly categorize interested structures. In addition, a localized transfer function is subsequently presented to assign optical parameters via interested information such as intensity, thickness and distance. As can be seen from the experimental results, the proposed techniques allow to appropriately visualize interested structures in highly complex volume medical data sets. © 2011 IEEE.

Citation

Xiang, D., Tian, J., Yang, F., Yang, Q., Zhang, X., Li, Q., & Liu, X. (2011). Skeleton cuts-An efficient segmentation method for volume rendering. IEEE Transactions on Visualization and Computer Graphics, 17(9), 1295-1306. https://doi.org/10.1109/tvcg.2010.239

• Journal Article Type: Article
• Acceptance Date: Aug 31, 2010
• Online Publication Date: Oct 29, 2010
• Publication Date: 2011-09
• Journal: IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
• Print ISSN: 1077-2626
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 9
• Pages: 1295-1306
• DOI: https://doi.org/10.1109/tvcg.2010.239
• Keywords: Signal Processing; Software; Computer Vision and Pattern Recognition; Computer Graphics and Computer-Aided Design
• Public URL: https://hull-repository.worktribe.com/output/405600
• Publisher URL: https://ieeexplore.ieee.org/document/5620899/