By Topic

Real time reconstruction of volumes from very large datasets using CUDA

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)

This article presents a memory efficient implementation of the Marching Cubes algorithm using NVIDIA's CUDA technology. The algorithm can handle datasets that are normally too large for current hardware by splitting the initial volume into several smaller subvolumes while minimizing extra computations caused by subvolume overlapping. Moreover, our approach is scalable, making it easy to benefit from additional computational resources.

Published in:

System Theory, Control, and Computing (ICSTCC), 2011 15th International Conference on

Date of Conference:

14-16 Oct. 2011