Out-of-Core Segmentation by Deformable Models

  • Gilson Giraldi
  • Leandro Schaefer
  • Ricardo Farias
  • Rodrigo Silva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2955)

Abstract

Memory limitations can lower the performance of segmentation applications for large images or even make it undoable. In this paper we address this problem through out-of-core techniques. Specifically, we integrate the T-Surfaces model, and out-of-core isosurface generation methods in a general framework for segmentation of large image volumes. T-Surfaces is a parametric deformable model based on a triangulation of the image domain, a discrete surface model and an image threshold. Isosurface generation techniques have been implemented through an out-of-core method that uses a k-d-tree-like structures, called meta-cell technique. By using the meta-cell framework, we present an out-of-core version of a segmentation method based on T-Surfaces and isosurface extraction. We demonstrate our out-of-core methodology (Meta-Cell, Isosurfaces, T-Surfaces) for segmentation of grey level images.

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References

  1. 1.
    Bruce, J., Balch, T., Veloso, M.: Fast and inexpensive color image segmentation for interactive robots (2000)Google Scholar
  2. 2.
    Chiang, Y.-J., Farias, R., Silva, C., Wei, B.: A unified infrastructure for parallel out-of-core isosurface and volume rendering of unstructured grids. IEEE Parallel and Large-Data Vis. and Graph. (2001)Google Scholar
  3. 3.
    Chiang, Y.-J., Silva, C., Schroeder, W.J.: Interactive out-of-core isosurface extraction. IEEE Visualization, 67–174 (1998)Google Scholar
  4. 4.
    Farias, R., Silva, C.: Out-of-core rendering of large unstructured grids. IEEE Computer Graphics & Applications 21(4), 42–50 (2001)CrossRefGoogle Scholar
  5. 5.
    Jain, A.K.: Fundamentals of Digital Image Processing. Prentice-Hall, Inc., Englewood Cliffs (1989)MATHGoogle Scholar
  6. 6.
    Kass, M., Witkin, A., Terzopoulos, D.: Snakes: Active contour models. International Journal of Computer Vision 1(4), 321–331 (1988)CrossRefMATHGoogle Scholar
  7. 7.
    McInerney, T., Terzopoulos, D.: Deformable models in medical image analysis: A survey. Medical Image Analysis 1(2) (1996)Google Scholar
  8. 8.
    McInerney, T., Terzopoulos, D.: Topology adaptive deformable surfaces for medical image volume segmentation. IEEE Trans. on Medical Imaging 18(10), 840–850 (1999)CrossRefGoogle Scholar
  9. 9.
    Strauss, E., Jimenez, W., Giraldi, G.A., Silva, R., Oliveira, A.F.: A semiautomatic surface reconstruction framework based on t-surfaces and isosurface extraction methods. In: International Symposium on Computer Graphics, Image Processing and Vision, SIBGRAPI (2002)Google Scholar
  10. 10.
    Sutton, P., Hansen, C.: Accelerated isosurface extraction in time-varying fields. IEEE Trans. on Visualization 6(2), 98–107 (2001)CrossRefGoogle Scholar
  11. 11.
    Ueng, S.-K., Sikorski, C., Ma, K.-L.: Out-of-core streamline visualization on large unstructured meshes. IEEE Trans. on Vis. and Computer Graphics 3(4), 370–380 (1997)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gilson Giraldi
    • 1
  • Leandro Schaefer
    • 1
  • Ricardo Farias
    • 1
  • Rodrigo Silva
    • 1
  1. 1.National Laboratory for Scientific ComputingLNCCPetrópolisBrazil

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