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Comparison of Feature Extraction Methods for Breast Cancer Detection

  • Rafael Llobet
  • Roberto Paredes
  • Juan C. Pérez-Cortés
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3523)

Abstract

Although screening mammography is widely used for the detection of breast tumors, it is difficult for a radiologist to interpret correctly a mammogram. It is possible to improve this task by using a computer aided diagnosis system (CAD) which highlights the areas most likely to contain cancer cells. In this paper, we present and compare five different feature extraction methods for breast cancer detection in digitized mammograms. All the methods are based on features extracted from a local window and on a k-nearest neighbor classifier with fast search.

Keywords

Feature Vector Digital Mammography Feature Extraction Method Breast Cancer Detection Digitize Mammogram 
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 2005

Authors and Affiliations

  • Rafael Llobet
    • 1
  • Roberto Paredes
    • 1
  • Juan C. Pérez-Cortés
    • 1
  1. 1.Instituto Tecnológico de InformáticaUniversidad Politécnica de ValenciaValenciaSpain

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