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Clustering through SOM Consistency

  • Nicolau Gonçalves
  • Ricardo Vigário
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7324)

Abstract

Clustering is a classical tool in image analysis, with wide applications. Yet, most of its algorithmic solutions include a considerable amount of stochasticity, e.g. due to different initialisations. Here, we introduce a clustering method rooted on self organizing maps, that exploits the maps’ intrinsic variability, to produce reliable clustering. Although only a subset of the data is consistently clustered, we show that this set is trustworthy, and can be used for posterior classification.

Keywords

Grey Matter Ground Truth Multiple Sclerosis Lesion Grand Challenge Competitive Learning 
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 2012

Authors and Affiliations

  • Nicolau Gonçalves
    • 1
  • Ricardo Vigário
    • 1
  1. 1.Department of Information and Computer ScienceAalto University School of ScienceAaltoFinland

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