Registration-Based Segmentation Using the Information Bottleneck Method

  • Anton Bardera
  • Miquel Feixas
  • Imma Boada
  • Jaume Rigau
  • Mateu Sbert
Conference paper

DOI: 10.1007/978-3-540-72849-8_17

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4478)
Cite this paper as:
Bardera A., Feixas M., Boada I., Rigau J., Sbert M. (2007) Registration-Based Segmentation Using the Information Bottleneck Method. In: Martí J., Benedí J.M., Mendonça A.M., Serrat J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg

Abstract

We present two new clustering algorithms for medical image segmentation based on the multimodal image registration and the information bottleneck method. In these algorithms, the histogram bins of two registered multimodal 3D-images are clustered by minimizing the loss of mutual information between them. Thus, the clustering of histogram bins is driven by the preservation of the shared information between the images, extracting from each image the structures that are more relevant to the other one. In the first algorithm, we segment only one image at a time, while in the second both images are simultaneously segmented. Experiments show the good behavior of the presented algorithms, especially the simultaneous clustering.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Anton Bardera
    • 1
  • Miquel Feixas
    • 1
  • Imma Boada
    • 1
  • Jaume Rigau
    • 1
  • Mateu Sbert
    • 1
  1. 1.Institut d’Informàtica i Aplicacions, Universitat de Girona 

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