Paper
30 May 2003 Combined approach of shell and shear-warp rendering for efficient volume visualization
Author Affiliations +
Abstract
In Medical Imaging, shell rendering (SR) and shear-warp rendering (SWR) are two ultra-fast and effective methods for volume visualization. We have previously shown that, typically, SWR can be on the average 1.38 times faster than SR, but it requires from 2 to 8 times more memory space than SR. In this paper, we propose an extension of the compact shell data structure utilized in SR to allow shear-warp factorization of the viewing matrix in order to obtain speed up gains for SR, without paying the high storage price of SWR. The new approach is called shear-warp shell rendering (SWSR). The paper describes the methods, points out their major differences in the computational aspects, and presents a comparative analysis of them in terms of speed, storage, and image quality. The experiments involve hard and fuzzy boundaries of 10 different objects of various sizes, shapes, and topologies, rendered on a 1GHz Pentium-III PC with 512MB RAM, utilizing surface and volume rendering strategies. The results indicate that SWSR offers the best speed and storage characteristics compromise among these methods. We also show that SWSR improves the rendition quality over SR, and provides renditions similar to those produced by SWR.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexandre Xavier Falcao, Leonardo M. Rocha, and Jayaram K. Udupa "Combined approach of shell and shear-warp rendering for efficient volume visualization", Proc. SPIE 5029, Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display, (30 May 2003); https://doi.org/10.1117/12.479765
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Volume rendering

Visualization

Fuzzy logic

Opacity

Volume visualization

Image quality

Binary data

Back to Top