Optimized GPU histograms for multi-modal registration
Siemens Corporate Research, Princeton, USA
IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011
@inproceedings{vetter2011optimized,
title={Optimized GPU histograms for multi-modal registration},
author={Vetter, C. and Westermann, R.},
booktitle={Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on},
pages={1227–1230},
year={2011},
organization={IEEE}
}
GPU-based systems are used more and more for medical image processing because of their parallel processing power and memory bandwidth. Impressive results have been achieved when registering large volume, however, one of themost-used similarity measures for multi-modal registration – mutual information – is not well suited for the streaming architecture because of its memory access pattern. We present two optimization approaches that improve the performance by a factor of four compared to state-of-the-art GPU algorithms in the latest research papers.
June 22, 2011 by hgpu
