Cost-effective medical image reconstruction: from clusters to graphics processing units

Maraike Schellmann, Jurgen Vording, Sergei Gorlatch, Dominik Meilander
University of Munster, Munster, Germany
In CF ’08: Proceedings of the 2008 conference on Computing frontiers (2008), pp. 283-292


   title={Cost-effective medical image reconstruction: from clusters to graphics processing units},

   author={Schellmann, M. and V{\”o}rding, J. and Gorlatch, S. and Meil{\”a}nder, D.},

   booktitle={Proceedings of the 5th conference on Computing frontiers},





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We demonstrate that for modern medical imaging applications, parallel implementations on traditional parallel architectures (clusters and multiprocessor servers) can be outperformed, both in terms of speed and cost-effectiveness, by new implementations on next-generation architectures like GPUs (Graphics Processing Units). Although, compared to clusters and multiprocessor servers, GPUs are rather small and much less expensive, they consist of several SIMD-processors and thus provide a high degree of parallelism. For an iterative image reconstruction algorithm—the list-mode OSEM— we demonstrate, first, the limitations of parallel reconstructions with this algorithm on the traditional parallel architectures, and second, how the well-analyzed parallel strategies for traditional architectures can be adapted systematically to achieve fast reconstructions on the GPU.
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