Iterative Reconstruction for Transmission Tomography on GPU Using Nvidia CUDA

被引：0
作者：
Damien Vintache [1 ]
Bernard Humbert [1 ]
David Brasse [1 ]
机构：
[1] Institut Pluridisciplinaire Hubert Curien,CNRS/IN2P3,23 rue du Loess BP28 67037 Strasbourg,France
来源：
Tsinghua Science and Technology | 2010年 / 15卷 / 01期
关键词：
tomography; image reconstruction; parallel processing;
D O I：
暂无
中图分类号：
TP391.41 [];
学科分类号：
080203 ;
摘要：
The iterative reconstruction algorithms for X-ray CT image reconstruction suffer from their high computational cost.Recently Nvidia releases common unified device architecture(CUDA),allowing developers to access to the processing power of Nvidia graphical processing units(GPUs),in order to perform general purpose computations.The use of the GPU,as an alternative computation platform,allows decreasing processing times,for parallel algorithms.This paper aims to demonstrate the feasibility of such an implementation for the iterative image reconstruction.The ordered subsets convex(OSC) algorithm,an iterative reconstruction algorithm for transmission tomography,has been developed with CUDA.The performances have been evaluated and compared with another implementation using a single CPU node.The result shows that speed-ups of two orders of magnitude,with a negligible impact on image accuracy,have been observed.
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收藏
页码：11 / 16
页数：6
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