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Histopathological Image Classification Using Stain Component Features on a pLSA Model

  • Gloria Díaz
  • Eduardo Romero
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6419)

Abstract

Semantic annotation of microscopical field of views is one of the key problems in computer assistance of histopathological images. In this paper a new method for extracting patch descriptors is proposed and evaluated using a probabilistic latent semantic analysis (pLSA) classification model. The proposed approach is based on the analysis of the different dyes used to stain the histological sample. This analysis allows to find local regions that correspond to cells in the image, which are then described by the SIFT descriptors of the stain components. The proposed approach outperforms the conventional sampling and description strategies, proposed in the literature.

Keywords

Semantic annotation Histopathological Images Color decomposition pLSA SIFT descriptors 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gloria Díaz
    • 1
  • Eduardo Romero
    • 1
  1. 1.Bioingenium Research GroupNational University of ColombiaBogotáColombia

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