Structure segmentation and recognition in images guided by structural constraint propagation

  • Authors:

  • Olivier Nempont;Jamal Atif;Elsa Angelini;Isabelle Bloch

  • Affiliations:

  • Telecom ParisTech, CNRS UMR 5141 LTCI, Paris, email: olivier.nempont@telecom-paristech.fr;Unité ESPACE S140, IRD-Cayenne/UAG, Guyane Française, email: jamal.atif@gmail.com;Telecom ParisTech, CNRS UMR 5141 LTCI, Paris, email: elsa.angelini@telecom-paristech.fr;Telecom ParisTech, CNRS UMR 5141 LTCI, Paris, email: isabelle.bloch@telecom-paristech.fr

  • Venue:
  • Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
  • Year:
  • 2008

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Abstract

In some application domains, such as medical imaging, the objects that compose the scene are known as well as some of their properties and their spatial arrangement. We can take advantage of this knowledge to perform the segmentation and recognition of structures in medical images. We propose here to formalize this problem as a constraint network and we perform the segmentation and recognition by iterative domain reductions, the domains being sets of regions. For computational purposes we represent the domains by their upper and lower bounds and we iteratively reduce the domains by updating their bounds. We show some preliminary results on normal and pathological brain images.