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Reconstruction of Patient-Specific 3D Bone Surface from 2D Calibrated Fluoroscopic Images and Point Distribution Model

  • Guoyan Zheng
  • Miguel Á. G. Ballester
  • Martin Styner
  • Lutz-Peter Nolte
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4190)

Abstract

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.

Keywords

point distribution model surface reconstruction 2D/3D correspondence extrapolation deformation thin-plate splines 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guoyan Zheng
    • 1
  • Miguel Á. G. Ballester
    • 1
  • Martin Styner
    • 2
  • Lutz-Peter Nolte
    • 1
  1. 1.MEM Research CenterUniversity of BernBernSwitzerland
  2. 2.Departments of Computer Science and PsychiatryUniversity of North Carolina at Chapel HillChapel HillUSA

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