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Optimal 3D surface reconstruction from a small number of conventional 2D X-ray images

  • Simant Prakoonwit
    ,
  • Benjamin Ralph
Research Output: Contribution to journal Article Peer-review

Abstract

This paper describes a method for reconstructing 3D frontier points, contour generators and surfaces of anatomical objects or smooth surfaces from a small number, e.g. 10, of conventional 2D X-ray images. The X-ray images are taken at different viewing directions with full prior knowledge of the X-ray source and sensor configurations. Unlike previous works, we empirically demonstrate that if the viewing directions are uniformly distributed around the object's viewing sphere, then the reconstructed 3D points automatically cluster closely on a highly curved part of the surface and are widely spread on smooth or flat parts. The advantage of this property is that the reconstructed points along a surface or a contour generator are not under-sampled or under-represented because surfaces or contours should be sampled or represented with more densely points where their curvatures are high. The more complex the contour's shape, the greater is the number of points required, but the greater the number of points is automatically generated by the proposed method. Given that the number of viewing directions is fixed and the viewing directions are uniformly distributed, the number and distribution of the reconstructed points depend on the shape or the curvature of the surface regardless of the size of the surface or the size of the object. The technique may be used not only in medicine but also in industrial applications.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 197

Journal (Volume, Issue Number)

Journal of X-Ray Science and Technology (Volume 15, Issue 4)

Publication milestones

  • Published - 01/01/2007

Publication status

Published - 01/01/2007

ISSN

0895-3996

External Publication IDs

  • handle.net: 10547/284303
  • Scopus: 37549009170

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