Accelerating Cone Beam Reconstruction Using the CUDA-Enabled GPU

  • Yusuke Okitsu
  • Fumihiko Ino
  • Kenichi Hagihara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5374)


Compute unified device architecture (CUDA) is a software development platform that enables us to write and run general-purpose applications on the graphics processing unit (GPU). This paper presents a fast method for cone beam reconstruction using the CUDA-enabled GPU. The proposed method is accelerated by two techniques: (1) off-chip memory access reduction; and (2) memory latency hiding. We describe how these techniques can be incorporated into CUDA code. Experimental results show that the proposed method runs at 82% of the peak memory bandwidth, taking 5.6 seconds to reconstruct a 5123-voxel volume from 360 5122-pixel projections. This performance is 18% faster than the prior method. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Yusuke Okitsu
    • 1
  • Fumihiko Ino
    • 1
  • Kenichi Hagihara
    • 1
  1. 1.Graduate School of Information Science and TechnologyOsaka UniversityOsakaJapan

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