A GPGPU Approach for Accelerating 2-D/3-D Rigid Registration of Medical Images

  • Fumihiko Ino
  • Jun Gomita
  • Yasuhiro Kawasaki
  • Kenichi Hagihara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4330)


This paper presents a fast 2-D/3-D rigid registration method using a GPGPU approach, which stands for general-purpose computation on the graphics processing unit (GPU). Our method is based on an intensity-based registration algorithm using biplane images. To accelerate this algorithm, we execute three key procedures of 2-D/3-D registration on the GPU: digitally reconstructed radiograph (DRR) generation, gradient image generation, and normalized cross correlation (NCC) computation. We investigate the usability of our method in terms of registration time and robustness. The experimental results show that our GPU-based method successfully completes a registration task in about 10 seconds, demonstrating shorter registration time than a previous method based on a cluster computing approach.


Graphic Processing Unit Graphic Hardware Normalize Cross Correlation Target Registration Error Graphic Processing Unit Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fumihiko Ino
    • 1
  • Jun Gomita
    • 2
  • Yasuhiro Kawasaki
    • 1
  • Kenichi Hagihara
    • 1
  1. 1.Graduate School of Information Science and TechnologyOsaka UniversityToyonaka, OsakaJapan
  2. 2.Graduate School of Information Science and TechnologyThe University of Tokyo 

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