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Fast 3D Reconstruction of the Spine Using User-Defined Splines and a Statistical Articulated Model

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Advances in Visual Computing (ISVC 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5875))

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Abstract

This paper proposes a method for rapidly reconstructing 3D models of the spine from two planar radiographs. For performing 3D reconstructions, users only have to identify on each radiograph a spline that represents the spine midline. Then, a statistical articulated model of the spine is deformed until it best fits these splines. The articulated model used on this method not only models vertebrae geometry, but their relative location and orientation as well.

The method was tested on 14 radiographic exams of patients for which reconstructions of the spine using a manual identification method where available. Using simulated splines, errors of 2.2±1.3mm were obtained on endplates location, and 4.1±2.1mm on pedicles. Reconstructions by non-expert users show average reconstruction times of 1.5min, and mean errors of 3.4mm for endplates and 4.8mm for pedicles.

These results suggest that the proposed method can be used to reconstruct the human spine in 3D when user interactions have to be minimised.

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Authors and Affiliations

  1. Lab. de Inteligência Artificial e de Ciência de Computadores, FEUP, Portugal

    Daniel C. Moura & Jorge G. Barbosa

  2. Faculdade de Engenharia, Dep. Eng. Informática, U. do Porto, Portugal

    Daniel C. Moura & Jorge G. Barbosa

  3. Instituto de Engenharia Mecânica e Gestão Industrial, Campus da FEUP, Portugal

    João Manuel R. S. Tavares

  4. Faculdade de Engenharia, Dep. de Eng. Mecânica, Rua Dr. Roberto Frias, U. do Porto, 4200-465, Porto, Portugal

    João Manuel R. S. Tavares

  5. National Research Council Canada, 1200, Montreal Rd, Ottawa, K1A 0R6, Canada

    Jonathan Boisvert

  6. École Polytechnique de Montréal, Montréal, QC, H3T 1J4, Canada

    Jonathan Boisvert

Authors
  1. Daniel C. Moura
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  2. Jonathan Boisvert
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  3. Jorge G. Barbosa
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  4. João Manuel R. S. Tavares
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada, Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. Graduate School of Science and Engineering, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama-shi, 338-8570, Saitama, Japan

    Yoshinori Kuno

  6. Institute for Infocomm Research, 21 Heng Mui Keng Terrace, P.O. Box, 119613, Singapore

    Junxian Wang

  7. Department of Computer Science & Information Engineering, Tamkang University, Tamsui, Taipei, Taiwan, R.O.C.

    Jun-Xuan Wang

  8. Microsoft Research, Redmond, WA, USA

    Junxian Wang

  9. Department of Informatics, Univ. of Zurich, Winterthurerstr. 190, P.O. Box, 8057, Zurich, Switzerland

    Renato Pajarola

  10. Lawrence Livermore National Laboratory, 94550, Livermore, CA, USA

    Peter Lindstrom

  11. University of Applied Sciences Bonn-Rhein-Sieg, 53754, Sankt Augustin, Germany

    André Hinkenjann

  12. Humana Inc., 40202, Louisville, KY, USA

    Miguel L. Encarnação

  13. SCI Institute & School of Computing, University of Utah, 84112, Salt Lake City, UT, USA

    Cláudio T. Silva

  14. Desert Research Institute, 89512, Reno, NV, USA

    Daniel Coming

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© 2009 Springer-Verlag Berlin Heidelberg

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Moura, D.C., Boisvert, J., Barbosa, J.G., Tavares, J.M.R.S. (2009). Fast 3D Reconstruction of the Spine Using User-Defined Splines and a Statistical Articulated Model. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2009. Lecture Notes in Computer Science, vol 5875. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10331-5_55

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  • DOI: https://doi.org/10.1007/978-3-642-10331-5_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10330-8

  • Online ISBN: 978-3-642-10331-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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