A Multiple Classifier System for Classification of Breast Lesions Using Dynamic and Morphological Features in DCE-MRI

  • Roberta Fusco
  • Mario Sansone
  • Antonella Petrillo
  • Carlo Sansone
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7626)

Abstract

In this paper we propose a Multiple Classifier System (MCS) for classifying breast lesions in Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI). The proposed MCS combines the results of two classifiers trained with dynamic and morphological features respectively. Twenty-one malignant and seventeen benign breast lesions, histologically proven, were analyzed. Volumes of Interest (VOIs) have been automatically extracted via a segmentation procedure assessed in a previous study. The performance of the MCS have been compared with histological classification. Results indicated that with automatic segmented VOIs 90% of test-set lesions were correctly classified.

Keywords

breast DCE-MRI multiple classification system morphological and dynamic features 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Roberta Fusco
    • 1
  • Mario Sansone
    • 1
  • Antonella Petrillo
    • 2
  • Carlo Sansone
    • 3
  1. 1.Department of Biomedical, Electronic and Telecommunication EngineeringUniversity Federico II of NaplesItaly
  2. 2.Department of Diagnostic ImagingNational Cancer Institute of Naples ‘Fondazione Pascale’Italy
  3. 3.Department of Computer and Systems EngineeringUniversity Federico II of NaplesItaly

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