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The role of GPU computing in medical image analysis and visualization

S. Moulik, W. Boonn
University of Pennsylvania, 3400 Spruce St. Philadelphia, PA 19104
Proc. SPIE 7967, 79670L, 2011

@inproceedings{moulik2011role,

   title={The role of GPU computing in medical image analysis and visualization},

   author={Moulik, S. and Boonn, W.},

   booktitle={Proceedings of SPIE},

   volume={7967},

   pages={79670L},

   year={2011}

}

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The role of computers in medical image display and analysis continues to be one of the most computationally demanding tasks facing modern computers. Recent advances in GPU architecture have allowed for a new programming paradigm which utilized the massively parallel computational capacity of GPUs for general purpose computing. These parallel processors provide substantial performance benefits in image analysis and manipulation. Automated segmentation algorithms gain the most benefit from incorporation of GPU computing into the image processing workflow. There are also new visualization paradigms, such as stereoscopic 3D, which have been made possible by the continued increase in computational capacity of GPUs. These two key functions of modern GPUs will enable medical imagers to keep pace with the increasing size of scan data sets while allowing for new and innovative analysis and interaction paradigms.
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