Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images
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 segmentat...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2011/640208 |
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| _version_ | 1850215790557528064 |
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| author | Fabian Lecron Sidi Ahmed Mahmoudi Mohammed Benjelloun Saïd Mahmoudi Pierre Manneback |
| author_facet | Fabian Lecron Sidi Ahmed Mahmoudi Mohammed Benjelloun Saïd Mahmoudi Pierre Manneback |
| author_sort | Fabian Lecron |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-829f4f1126fb4efcb623062d736d3cd5 |
| institution | OA Journals |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-829f4f1126fb4efcb623062d736d3cd52025-08-20T02:08:31ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962011-01-01201110.1155/2011/640208640208Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray ImagesFabian Lecron0Sidi Ahmed Mahmoudi1Mohammed Benjelloun2Saïd Mahmoudi3Pierre Manneback4Computer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, BelgiumComputer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, BelgiumComputer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, BelgiumComputer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, BelgiumComputer Science Department, Faculty of Engineering, University of Mons, Place du Parc, 20 7000 Mons, BelgiumThe 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.http://dx.doi.org/10.1155/2011/640208 |
| spellingShingle | Fabian Lecron Sidi Ahmed Mahmoudi Mohammed Benjelloun Saïd Mahmoudi Pierre Manneback Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images International Journal of Biomedical Imaging |
| title | Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images |
| title_full | Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images |
| title_fullStr | Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images |
| title_full_unstemmed | Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images |
| title_short | Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images |
| title_sort | heterogeneous computing for vertebra detection and segmentation in x ray images |
| url | http://dx.doi.org/10.1155/2011/640208 |
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