Automatic Lung Surface Registration Using Selective Distance Measure in Temporal CT Scans

  • Helen Hong
  • Jeongjin Lee
  • Kyung Won Lee
  • Yeong Gil Shin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)

Abstract

In this paper, we propose a novel technique of lung surface registration for investigating temporal changes such as growth rates of pulmonary nodules. For the registration of a pair of CT scans, a proper geometrical transformation is found through the following steps: First, optimal cube registration is performed for the initial gross registration. Second, for allowing fast and robust convergence on the optimal value, a 3D distance map is generated by the local distance propagation. Third, the distance measure between surface boundary points is repeatedly evaluated by the selective distance measure. Experimental results show that the performance of our registration method is very promising compared with conventional methods in the aspects of its computation time androbustness.

Keywords

Target Volume Chest Compute Tomography Pulmonary Nodule Iterative Close Point Initial Registration 
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.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Helen Hong
    • 1
  • Jeongjin Lee
    • 2
  • Kyung Won Lee
    • 3
  • Yeong Gil Shin
    • 2
  1. 1.School of Electrical Engineering and Computer Science BK21: Information TechnologySeoul National UniversitySeoulKorea
  2. 2.School of Electrical Engineering and Computer ScienceSeoul National University 
  3. 3.Dept. of RadiologySeoul National University Bundang HospitalKyunggi-doKorea

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