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.
引用
收藏
页码：11 / 16
页数：6
相关论文
共 17 条
  • [11] Comparison of high-speed ray casting on GPU using CUDA and openGL. Weinlich A,,Keck B,Scherl H, et al. Proceedings of the First International Workshop on New Frontiers in High-Performance and Hardware-Aware Computing . 2008
  • [12] A statistical approach to high-quality CT reconstruction at low radiation doses for real-time guidance and navigation. Shetye A,Shekhar R. Proceedings of SPIE Medical Imaging 2007 . 2007
  • [13] A faster orederd-subset convex algo- rithm for iterative reconstruction in rotation-free micro-CT system. Quan E,Lalush D S. Physics in Medicine and Biology . 2009
  • [14] Practical cone-beam algorithm. Feldkamp LA,Davis LC,Kress JW. Journal of the Optical Society of America A: Optics, Image Science and Vision . 1984
  • [15] GPU-based paral- lel-beam and cone-beam forward-and backprojection us- ing CUDA. Knaup M,Steckmann S,Kachelrieβ M. Proceedings of 2008 IEEE Nuclear Science Symposium Conference . 2008
  • [16] Accelerating backprojec- tions via CUDA architecture. Yang H,Li M,Koizumi K, et al. Proceedings of the 9th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine . 2007
  • [17] Quality of statistical reconstruction in medical CT. Kachelrieβ M,Berkus T,Kalender W. Proceedings of IEEE Nuclear Science Symposium Conference . 2003
12