Parallel computation of mutual information on the GPU with application to real-time registration of 3D medical images
College of Engineering and Computer Science (CECS), The Australian National University, Canberra, ACT 0200, Australia
Computer Methods and Programs in Biomedicine, Volume 99, Issue 2, Pages 133-146 (August 2010)
@article{shams2010parallel,
title={Parallel computation of mutual information on the GPU with application to real-time registration of 3D medical images},
author={Shams, R. and Sadeghi, P. and Kennedy, R. and Hartley, R.},
journal={Computer methods and programs in biomedicine},
volume={99},
number={2},
pages={133–146},
issn={0169-2607},
year={2010},
publisher={Elsevier}
}
Due to processing constraints, automatic image-based registration of medical images has been largely used as a pre-operative tool. We propose a novel method named sort and count for efficient parallelization of mutual information (MI) computation designed for massively multi-processing architectures. Combined with a parallel transformation implementation and an improved optimization algorithm, our method achieves real-time (less than 1 s) rigid registration of 3D medical images using a commodity graphics processing unit (GPU). This represents a more than 50-fold improvement over a standard implementation on a CPU. Real-time registration opens new possibilities for development of improved and interactive intraoperative tools that can be used for enhanced visualization and navigation during an intervention.
November 23, 2010 by hgpu
