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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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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