Mutual information criterion for feature selection with application to classification of breast microcalcifications

Idit Diamant, Moran Shalhon, Jacob Goldberger, Hayit Greenspan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Classification of clustered breast microcalcifications into benign and malignant categories is an extremely challenging task for computerized algorithms and expert radiologists alike. In this paper we present a novel method for feature selection based on mutual information (MI) criterion for automatic classification of microcalcifications. We explored the MI based feature selection for various texture features. The proposed method was evaluated on a standardized digital database for screening mammography (DDSM). Experimental results demonstrate the effectiveness and the advantage of using the MI-based feature selection to obtain the most relevant features for the task and thus to provide for improved performance as compared to using all features.

Original languageEnglish
Title of host publicationMedical Imaging 2016
Subtitle of host publicationImage Processing
EditorsMartin A. Styner, Elsa D. Angelini, Elsa D. Angelini
ISBN (Electronic)9781510600195
StatePublished - 2016
EventMedical Imaging 2016: Image Processing - San Diego, United States
Duration: 1 Mar 20163 Mar 2016

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2016: Image Processing
Country/TerritoryUnited States
CitySan Diego

Bibliographical note

Publisher Copyright:
© 2016 SPIE.


  • Computer-aided diagnosis (CADx)
  • Feature selection
  • Mammography
  • Microcalcifications
  • Mutual information
  • Texture features


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