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Multi-agent Approach for Image Processing: A Case Study for MRI Human Brain Scans Interpretation

  • Nathalie Richard
  • Michel Dojat
  • Catherine Garbay
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2780)

Abstract

Image interpretation consists in finding a correspondence between radiometric information and symbolic labelling with respect to specific spatial constraints. To cope with the difficulty of image interpretation, several information processing steps are required to gradually extract information from the image grey levels and to introduce symbolic information. In this paper, we evaluate the use of situated cooperative agents as a framework for managing such steps. Dedicated agent behaviours are dynamically adapted function of their position in the image, topographic relationships and radiometric information available. Acquired knowledge is diffused to acquaintance and incremental refinement of interpretation is obtained through focalisation and coordination of agents tasks. Based on several experiments on real images we demonstrate the potential interest of multi-agents for MRI brain scans interpretation.

Keywords

Magnetic Resonance Image Brain Bias Field Interpretation Process Local Histogram Magnetic Resonance Image Brain Scan 
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 2003

Authors and Affiliations

  • Nathalie Richard
    • 1
    • 2
  • Michel Dojat
    • 1
    • 2
  • Catherine Garbay
    • 2
  1. 1.Institut National de la Santé et de la Recherche Médicale, U594 – NeuroimagerieFonctionnelle et Métabolique, CHU – Pavillon BGrenobleFrance
  2. 2.Laboratoire TIMC-IMAG, Institut BonniotFaculté de Médecine, Domaine de la MerciLa TroncheFrance

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