A cooperative and adaptive approach to medical image segmentation

  • C. Spinu
  • C. Garbay
  • J. M. Chassery
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 934)


The purpose of the paper is to discuss the potential of a multi-agent approach for low-level image analysis. The work is based on the assumption that low-level processings should be adjusted locally, on zones of given characteristics, and be applied in an iterative framework with careful evaluation and control. A multi-agent architecture has been designed to this end, which allows to develop a dedicated low-level analysis strategy for each detected zone in the image. This analysis is based on an initial segmentation result, obtained as the fusion of two maps: a noise map and a texture map, representing regions with similar noise or texture characteristics. For each zone, a filtering / edge detection strategy is carefully selected and adjusted, based on evaluating the resulting edge map. The results are finally combined in a global segmentation image. The potential of the approach is illustrated on a natural MRI image.


Edge Detection Multiplicative Noise Impulsive Noise Medical Image Analysis Medical Image 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 1995

Authors and Affiliations

  • C. Spinu
    • 1
  • C. Garbay
    • 1
  • J. M. Chassery
    • 1
  1. 1.Faculté de médecine - Domaine de la MerciLab. TIMC / IMAG - Institut Albert BonniotLa Tronche CedexFrance

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