Acceleration of the speed of tissue characterization algorithm for coronary plaque by employing GPGPU technique
Tokuyama College of Technology, Dept. of Computer Science and Electrical Eng., Shunan, Japan
Proceedings of the 11th WSEAS international conference on robotics, control and manufacturing technology, and 11th WSEAS international conference on Multimedia systems & signal processing, ROCOM’11/MUSP’11, 2011
@inproceedings{koga2011acceleration,
title={Acceleration of the speed of tissue characterization algorithm for coronary plaque by employing GPGPU technique},
author={Koga, T. and Furukawa, S. and Suetake, N. and Uchino, E.},
booktitle={Proceedings of the 11th WSEAS international conference on robotics, control and manufacturing technology, and 11th WSEAS international conference on Multimedia systems & signal processing},
pages={52–57},
year={2011},
organization={World Scientific and Engineering Academy and Society (WSEAS)}
}
The general purpose computation technique on Graphics Processing Unit (GPGPU) has got into the limelight recently. The authors have proposed the multiple k-nearest neighbor (MkNN) classifier for the tissue characterization of coronary plaque. Its characterization performance is highly evaluated. The purpose of this paper is to accelerate the speed of MkNN classifier aiming for it to be actually used in the medical practice. It has been confirmed that its speed is drastically accelerated enough for the practical use.
September 22, 2011 by hgpu
