Mulitifractal Analysis with Lacunarity for Microcalcification Segmentation

  • Ines Slim
  • Hanen Bettaieb
  • Asma Ben Abdallah
  • Imen Bhouri
  • Mohamed Hedi Bedoui
Conference paper
Part of the Advances in Predictive, Preventive and Personalised Medicine book series (APPPM, volume 10)


The aim of this study is the microcalcification segmentation in digital mammograms. We propose two different methods which are based on the combination of the multifractal analysis with, respectively, the fractal analysis and then with the lacunarity. Our approach consists of two steps. On the first stage, we created the “α_image.” This image was constructed by singularity coefficient deduced from multifractal spectrum of the original image. On the second stage, in order to enhance the visualization of microcalcifications, we create the “f(α)_image” based on global regularity measure of “α_image.” Two different techniques are used: the box counting (BC) used to calculate fractal dimension and the gliding box method used to measure lacunarity. These techniques were applied in order to compare results. Our proposed approaches were tested on mammograms from “MiniMIAS database.” Results demonstrate that microcalcifications were successfully segmented.


Multifractal Fractal Lacunarity Microcalcifications Segmentation 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ines Slim
    • 1
  • Hanen Bettaieb
    • 1
  • Asma Ben Abdallah
    • 1
  • Imen Bhouri
    • 2
  • Mohamed Hedi Bedoui
    • 1
  1. 1.Laboratory of Technology and medical imagery, TIMFaculty of MedecineMonastirTunisia
  2. 2.Multifractals and wavelet research unitFaculty of sciencesMonastirTunisia

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