文章基本信息

标题：Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images
本地全文：下载
作者：Fabian Lecron ; Sidi Ahmed Mahmoudi ; Mohammed Benjelloun 等
期刊名称：International Journal of Biomedical Imaging
印刷版ISSN：1687-4188
电子版ISSN：1687-4196
出版年度：2011
卷号：2011
DOI：10.1155/2011/640208
出版社：Hindawi Publishing Corporation
摘要：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.