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International Journal of Biomedical Imaging
Volume 2011 (2011), Article ID 640208, 12 pages
Research Article

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

Computer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, Belgium

Received 8 March 2011; Accepted 3 June 2011

Academic Editor: Yasser M. Kadah

Copyright © 2011 Fabian Lecron et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.