Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms

  • Jelena Bozek
  • Michiel Kallenberg
  • Mislav Grgic
  • Nico Karssemeijer
Conference paper

DOI: 10.1007/978-3-642-31271-7_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7361)
Cite this paper as:
Bozek J., Kallenberg M., Grgic M., Karssemeijer N. (2012) Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms. In: Maidment A.D.A., Bakic P.R., Gavenonis S. (eds) Breast Imaging. IWDM 2012. Lecture Notes in Computer Science, vol 7361. Springer, Berlin, Heidelberg

Abstract

The size of a lesion is a feature often used in computer-aided detection systems for classification between benign and malignant lesions. However, size of a lesion presented by its area might not be as reliable as volume of a lesion. Volume is more independent of the view (CC or MLO) since it represents three dimensional information, whereas area refers only to the projection of a lesion on a two dimensional plane. Furthermore, volume might be better than area for comparing lesion size in two consecutive exams and for evaluating temporal change to distinguish benign and malignant lesions. We have used volumetric breast density estimation in digital mammograms to obtain thickness of dense tissue in regions of interest in order to compute volume of lesions. The dataset consisted of 382 mammogram pairs in CC and MLO views and 120 mammogram pairs for temporal analysis. The obtained correlation coefficients between the lesion size in the CC and MLO views were 0.70 (0.64-0.76) and 0.83 (0.79-0.86) for area and volume, respectively. Two-tailed z-test showed a significant difference between two correlation coefficients (p=0.0001). The usage of area and volume in temporal analysis of mammograms has been evaluated using ROC analysis. The obtained values of the area under the curve (AUC) were 0.73 and 0.75 for area and volume, respectively. Although a higher AUC value for volume was found, this difference was not significant (p=0.16).

Keywords

digital mammography temporal change lesion classification CAD breast density 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Jelena Bozek
    • 1
  • Michiel Kallenberg
    • 2
  • Mislav Grgic
    • 1
  • Nico Karssemeijer
    • 2
  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia
  2. 2.Department of RadiologyRadboud University Nijmegen Medical CentreNijmegenThe Netherlands

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