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Multi-scale gradient magnitude watershed segmentation

  • Ole Fogh Olsen
  • Mads Nielsen
Session 1: Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)

Abstract

A partitioning of an nD image is defined as the watersheds of some locally computable inhomogeneity measure. Dependent on the scale of the inhomogeneity measure a coarse or fine partitioning is defined. By analysis of the structural changes (catastrophes) in the measure introduced when scale is increased, a multi-scale linking of segments can be defined. This paper describes the multi-scale linking based on recent results of the deep structure of the squared gradient field[1]. An interactive semi-automatic segmentation tool, and results on synthetic and real 3D medical images are presented.

Keywords

Dissimilarity Measure Gradient Magnitude Catastrophe Theory Texture Segmentation Catchment Basin 
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 1997

Authors and Affiliations

  • Ole Fogh Olsen
    • 1
  • Mads Nielsen
    • 2
  1. 1.DIKUUniversity of CopenhagenCopenhagen EDenmark
  2. 2.3D-Lab, School of DentistryUniversity of CopenhagenDenmark

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