A Method for Detection and Modeling of the Human Spine Based on Principal Curvatures

  • Y. Santiesteban
  • J. M. Sanchiz
  • J. M. Sotoca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)


The detection and modeling of the human spine from scanned 3D data is an important issue in biomedical shape analysis. It can be useful for avoiding invasive treatments like radiographs, taken for the purpose of monitoring spine deformations and its correction, as is the cases in scoliosis. This is especially important with children.

This work presents a new method for the detection of the human spine from 3D models of human backs formed by triangular meshes, and taken with a range sensor. The method is based on the estimation of the principal curvatures directions, and by joining valley points along these directions. Results are presented with the method applied to scanned 3D models of real patients.


Principal Curvature Triangular Mesh Geodesic Distance Back Surface Cluster Centroid 
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

  • Y. Santiesteban
    • 1
  • J. M. Sanchiz
    • 2
  • J. M. Sotoca
    • 2
  1. 1.Universidad de OrienteSantiago de CubaCuba
  2. 2.Universidad Jaume ICastellónSpain

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