heterogeneous computing for vertebra detection and segmentation in x-ray images
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ID: 221675
2011
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Abstract
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.
| Reference Key |
lecron2011internationalheterogeneous
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|---|---|
| Authors | ;Fabian Lecron;Sidi Ahmed Mahmoudi;Mohammed Benjelloun;Saïd Mahmoudi;Pierre Manneback |
| Journal | Chemistry, an Asian journal |
| Year | 2011 |
| DOI |
10.1155/2011/640208
|
| URL | |
| Keywords |
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