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Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images

Fabian Lecron, Sidi Ahmed Mahmoudi, Mohammed Benjelloun, Said Mahmoudi, Pierre Manneback
Computer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, Belgium
International Journal of Biomedical Imaging, Volume 2011, Article ID 640208, 2011

@article{fabian2011heterogeneous,

   title={Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images},

   author={Fabian, L. and Sidi Ahmed, M. and Mohammed, B. and Pierre, M. and others},

   journal={International Journal of Biomedical Imaging},

   volume={2011},

   year={2011},

   publisher={Hindawi Publishing Corporation}

}

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The context of this work is related to the vertebra segmentation. The method we propose is based on the active shape model (ASM). An original approach taking advantage of the edge polygonal approximation was developed to locate the vertebra positions in a X-ray image. Despite the fact that segmentation results show good efficiency, the time is a key variable that has always to be optimized in a medical context. Therefore, we present how vertebra extraction can efficiently be performed in exploiting the full computing power of parallel (GPU) and heterogeneous (multi-CPU/multi-GPU) architectures. We propose a parallel hybrid implementation of the most intensive steps enabling to boost performance. Experimentations have been conducted using a set of high-resolution X-ray medical images, showing a global speedup ranging from 3 to 22, by comparison with the CPU implementation. Data transfer times between CPU and GPU memories were included in the execution times of our proposed implementation.
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