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Histopathology Image Classification Using Bag of Features and Kernel Functions

  • Juan C. Caicedo
  • Angel Cruz
  • Fabio A. Gonzalez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5651)

Abstract

Image representation is an important issue for medical image analysis, classification and retrieval. Recently, the bag of features approach has been proposed to classify natural scenes, using an analogy in which visual features are to images as words are to text documents. This process involves feature detection and description, construction of a visual vocabulary and image representation building through visual-word occurrence analysis. This paper presents an evaluation of different representations obtained from the bag of features approach to classify histopathology images. The obtained image descriptors are processed using appropriate kernel functions for Support Vector Machines classifiers. This evaluation includes extensive experimentation of different strategies, and analyses the impact of each configuration in the classification result.

Keywords

Kernel Function Image Retrieval Image Representation Feature Representation Natural Scene 
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

  • Juan C. Caicedo
    • 1
  • Angel Cruz
    • 1
  • Fabio A. Gonzalez
    • 1
  1. 1.Bioingenium Research GroupNational University of ColombiaColombia

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