WILF 2005: Fuzzy Logic and Applications pp 334-343 | Cite as

Mass Detection in Mammograms Using Gabor Filters and Fuzzy Clustering

  • M. Santoro
  • R. Prevete
  • L. Cavallo
  • E. Catanzariti
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3849)

Abstract

In this paper we describe a new segmentation scheme to detect masses in breast radiographs.

Our segmentation method relies on the well known fuzzy c-means unsupervised clustering technique using an image representation scheme based on the local power spectrum obtained by a bank of Gabor filters.

We tested our method on 200 mammograms from the CALMA database. The detected regions have been validated by comparing them with the radiologist’s hand-sketched boundaries of real masses. The results, evaluated using ROC curve methodology, show that the greater flexibility and effectiveness provided by the fuzzy clustering approach benefit from an image representation that combine both intensity and local frequency information.

Keywords

Fuzzy Cluster Gabor Filter Segmentation Scheme Mammographic Image Breast Region 
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 2006

Authors and Affiliations

  • M. Santoro
    • 1
  • R. Prevete
    • 1
  • L. Cavallo
    • 1
  • E. Catanzariti
    • 1
  1. 1.Department of Physical SciencesUniversity of Naples Federico II, INFN, Section of Naples 

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