Hardware-Accelerated Raycasting: Towards an Effective Brain MRI Visualization
Faculty of Computer Science and Informtion Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia
arXiv:1211.5595 [cs.CG] (22 Nov 2012)
@article{2012arXiv1211.5595A,
author={Adeshina}, A.~M. and {Hashim}, R. and {Khalid}, N.~E.~A. and {Abidin}, S.~Z.~Z.},
title={"{Hardware-Accelerated Raycasting: Towards an Effective Brain MRI Visualization}"},
journal={ArXiv e-prints},
archivePrefix={"arXiv"},
eprint={1211.5595},
primaryClass={"cs.CG"},
keywords={Computer Science – Computational Geometry},
year={2012},
month={nov},
adsurl={http://adsabs.harvard.edu/abs/2012arXiv1211.5595A},
adsnote={Provided by the SAO/NASA Astrophysics Data System}
}
The rapid development in information technology has immensely contributed to the use of modern approaches for visualizing volumetric data. Consequently, medical volume visualization is increasingly attracting attention towards achieving an effective visualization algorithm for medical diagnosis and pre-treatment planning. Previously, research has been addressing implementation of algorithm that can visualize 2-D images into 3-D. Meanwhile, achieving such a rendering algorithm at an interactive speed and of good robustness to handle mass data still remains a challenging issue. However, in medical diagnosis, finding the exact location of brain tumor or diseases is an important step of surgery / disease management. This paper proposes a GPU-based raycasting algorithm for accurate allocation and localization of human brain abnormalities using magnetic resonance (MRI) images of normal and abnormal patients.
November 27, 2012 by hgpu
