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A General Framework for Image Segmentation Using Ordered Spatial Dependency

  • Mikaël Rousson
  • Chenyang Xu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

The segmentation problem appears in most medical imaging applications. Many research groups are pushing toward a whole body segmentation based on atlases. With a similar objective, we propose a general framework to segment several structures. Rather than inventing yet another segmentation algorithm, we introduce inter-structure spatial dependencies to work with existing segmentation algorithms. Ranking the structures according to their dependencies, we end up with a hierarchical approach that improves each individual segmentation and provides automatic initializations. The best ordering of the structures can be learned off-line. We apply this framework to the segmentation of several structures in brain MR images.

Keywords

Image Segmentation Spatial Dependency Segmentation Algorithm Active Contour Hierarchical Segmentation 
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

  • Mikaël Rousson
    • 1
  • Chenyang Xu
    • 1
  1. 1.Department of Imaging and VisualizationSiemens Corporate ResearchPrinceton

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