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 50 条
  • [31] CUDA-based GPU computing for fast tomography visualisations
    Saxena, N.
    Baheti, G. L.
    Tripathi, D. K.
    Songara, K. C.
    Meghwal, L. R.
    Meena, V. L.
    INSIGHT, 2010, 52 (05) : 262 - 264
  • [32] Real Time Ultrasound Image Denoising Using NVIDIA CUDA
    Fredj, Amira Hadj
    Malek, Jihene
    2016 2ND INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP), 2016, : 136 - 140
  • [33] Belief Propagation Implementation Using CUDA on an NVIDIA GTX 280
    Xu, Yanyan
    Chen, Hui
    Klette, Reinhard
    Liu, Jiaju
    Vaudrey, Tobi
    AI 2009: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2009, 5866 : 180 - +
  • [34] IMPLEMENTATION OF USUAL COMPUTERIZED TOMOGRAPHY METHODS ON GPU USING THE COMPUTE UNIFIED DEVICE ARCHITECTURE (CUDA)
    Recur, Benoit
    Desbarats, Pascal
    Domenger, Jean-Philippe
    SPA 2009: SIGNAL PROCESSING ALGORITHMS, ARCHITECTURES, ARRANGEMENTS, AND APPLICATIONS CONFERENCE PROCEEDINGS, 2009, : 41 - 46
  • [35] Multiple string matching on a GPU using CUDA
    Kouzinopoulos, Charalampos S.
    Michailidis, Panagiotis D.
    Margaritis, Konstantinos G.
    Scalable Computing, 2015, 16 (02): : 121 - 137
  • [36] Canny Edge Detection on GPU using CUDA
    Horvath, Matthew, Jr.
    Bowers, Michael
    Alawneh, Shadi
    2023 IEEE 13TH ANNUAL COMPUTING AND COMMUNICATION WORKSHOP AND CONFERENCE, CCWC, 2023, : 419 - 425
  • [37] MULTIPLE STRING MATCHING ON A GPU USING CUDA
    Kouzinopoulos, Charalampos S.
    Michailidis, Panagiotis D.
    Margaritis, Konstantinos G.
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2015, 16 (02): : 121 - 137
  • [38] Parallelization and Optimization of SIFT on GPU Using CUDA
    Zhou, Yonglong
    Mei, Kuizhi
    Ji, Xiang
    Dong, Peixiang
    2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC), 2013, : 1351 - 1358
  • [39] GPU Acceleration using CUDA for Computational Electromagnetics
    Sideris, Constantine
    2024 INTERNATIONAL APPLIED COMPUTATIONAL ELECTROMAGNETICS SOCIETY SYMPOSIUM, ACES 2024, 2024,
  • [40] String Matching on a multicore GPU using CUDA
    Kouzinopoulos, Charalampos S.
    Margaritis, Konstantinos G.
    13TH PANHELLENIC CONFERENCE ON INFORMATICS, PROCEEDINGS, 2009, : 14 - 18
12345