A Novel Projection Based Approach for Medical Image Registration

  • Ali Khamene
  • Razvan Chisu
  • Wolfgang Wein
  • Nassir Navab
  • Frank Sauer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4057)


In this paper, we propose a computationally efficient method for medical image registration. The centerpiece of the approach is to reduce the dimensions of each image via a projection operation. The two sequences of projection images corresponding to each image are used for estimating the registration parameters. Depending upon how the projection geometry is set up, the lower dimension registration problem can be parameterized and solved for a subset of parameters from the original problem. Computation of similarity metrics on the lower dimension projection images is significantly less complex than on the original volumetric images. Furthermore, depending on the type of projection operator used, one can achieve a better signal to noise ratio for the projection images than the original images. In order to further accelerate the process, we use Graphic Processing Units (GPUs) for generating projections of the volumetric data. We also perform the similarity computation on the graphics board, using a GPU with a programmable rendering pipeline. By doing that, we avoid transferring a large amount of data from graphics memory to system memory for computation. Furthermore, the performance of the more complex algorithms exploiting the graphics processor’s capabilities is greatly improved. We evaluate the performance and the speed of the proposed projection based registration approach using various similarity measures and benchmark them against an SSE-accelerated CPU based implementation.


Similarity Measure Graphic Processing Unit Image Registration Projection Image Target Registration Error 
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

  • Ali Khamene
    • 1
  • Razvan Chisu
    • 2
  • Wolfgang Wein
    • 2
  • Nassir Navab
    • 2
  • Frank Sauer
    • 1
  1. 1.Imaging and Visualization Dept.Siemens Corporate ResearchPrincetonUSA
  2. 2.TU MunichComputer Aided Medical Procedures (CAMP) GroupGarchingGermany

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