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Visual Pattern Analysis in Histopathology Images Using Bag of Features

  • Angel Cruz-Roa
  • Juan C. Caicedo
  • Fabio A. González
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

This paper presents a framework to analyse visual patterns in a collection of medical images in a two stage procedure. First, a set of representative visual patterns from the image collection is obtained by constructing a visual-word dictionary under a bag-of-features approach. Second, an analysis of the relationships between visual patterns and semantic concepts in the image collection is performed. The most important visual patterns for each semantic concept are identified using correlation analysis. A matrix visualization of the structure and organization of the image collection is generated using a cluster analysis. The experimental evaluation was conducted on a histopathology image collection and results showed clear relationships between visual patterns and semantic concepts, that in addition, are of easy interpretation and understanding.

Keywords

Basal Cell Carcinoma Visual Word Visual Pattern Semantic Concept Cystic Change 
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 2009

Authors and Affiliations

  • Angel Cruz-Roa
    • 1
  • Juan C. Caicedo
    • 1
  • Fabio A. González
    • 1
  1. 1.Bioingenium Research GroupUniversidad Nacional de Colombia 

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