Breast Density Segmentation Using Texture

  • Styliani Petroudi
  • Michael Brady
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4046)


This paper describes an algorithm to segment mammo- graphic images into regions corresponding to different densities. The breast parenchymal segmentation uses information extracted for statistical texture based classification which is in turn incorporated in multi-vector Markov Random Fields. Such segmentation is key to developing quantitative mammographic analysis. The algorithm’s performance is evaluated quantitatively and qualitatively and the results show the feasibility of segmenting different mammographic densities.


Segmentation Algorithm Mammographic Density Digital Mammography Parenchymal Pattern Iterate Conditional Mode 
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

  • Styliani Petroudi
    • 1
  • Michael Brady
    • 1
  1. 1.Wolfson Medical Vision LaboratoryOxford UniversityOxfordUnited Kingdom

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