Multimodal Prior Appearance Models Based on Regional Clustering of Intensity Profiles

  • François Chung
  • Hervé Delingette
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5762)


Model-based image segmentation requires prior information about the appearance of a structure in the image. Instead of relying on Principal Component Analysis such as in Statistical Appearance Models, we propose a method based on a regional clustering of intensity profiles that does not rely on an accurate pointwise registration. Our method is built upon the Expectation-Maximization algorithm with regularized covariance matrices and includes spatial regularization. The number of appearance regions is determined by a novel model order selection criterion. The prior is described on a reference mesh where each vertex has a probability to belong to several intensity profile classes.


Posterior Probability Covariance Matrice Appearance Model Regional Cluster Cluster Validity Index 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • François Chung
    • 1
  • Hervé Delingette
    • 1
  1. 1.Asclepios Research TeamINRIA Sophia-AntipolisFrance

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