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Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies pp 187–225Cite as

Surface Reconstruction and Geometric Modeling for Digital Prosthesis Design

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Abstract

The restoration and recovery of a defective skull can be performed through operative techniques to implant a customized prosthesis. Recently, image processing, surface reconstruction, and geometric methods have been used for digital prosthesis design. In this chapter, we review state-of-the-art approaches in this field and discuss related issues. The field of prosthesis modeling may include methods for segmentation and surface reconstruction, geometric modeling, multiscale methods, and user interaction approaches. So, we present the background in the area by reviewing methods in isosurface extraction from 3D images, deformable models, wavelets, and subdivision surfaces. Then, we discuss some proposals in this area: a balloon model for slice-by-slice bone reconstruction, the T-Surfaces plus isosurface generation models as a general framework for surface reconstruction and user interaction, wavelets-based multiscale methods, and filling holes methods. We describe also experimental results and a computational tool that we are developing for image processing and visualization which can be used for digital prosthesis design. We offer a discussion by presenting some perspectives and issues related to the models described on previous sections. Finally, we present the conclusions of our work.

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Acknowledgements

The authors would like to thank CNPq (grant 133865/2009-6) and INCT-MACC for financial support.

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Authors and Affiliations

  1. National Laboratory for Scientific Computing, Petrópolis, Brazil

    Luiz C. M. de Aquino

Authors
  1. Luiz C. M. de Aquino
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  2. Gilson A. Giraldi
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  3. Paulo S. S. Rodrigues
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  4. Antônio Lopes A. Junior
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  5. Jaime S. Cardoso
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  6. Jasjit S. Suri
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Corresponding author

Correspondence to Luiz C. M. de Aquino .

Editor information

Editors and Affiliations

  1. , Department of Bioengineering, University of Louisville, Louisville, 40208, USA

    Ayman S. El-Baz

  2. School of Engineering, Ngee Ann Polytechnic, Clementi Road 535, Singapore, 599489, Singapore

    Rajendra Acharya U

  3. , Department of Biomedical Engineering, Columbia University, New York, 10027, New York, USA

    Andrew F. Laine

  4. Biomedical Technologies, Inc., Denver, Colorado, USA

    Jasjit S. Suri

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de Aquino, L.C.M., Giraldi, G.A., Rodrigues, P.S.S., Junior, A.L.A., Cardoso, J.S., Suri, J.S. (2011). Surface Reconstruction and Geometric Modeling for Digital Prosthesis Design. In: El-Baz, A., Acharya U, R., Laine, A., Suri, J. (eds) Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8204-9_8

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