Microcalcification Detection in Mammograms Based on Fuzzy Logic and Cellular Automata

  • Yoshio RubioEmail author
  • Oscar Montiel
  • Roberto Sepúlveda
Part of the Studies in Computational Intelligence book series (SCI, volume 667)


In the early diagnosis of breast cancer, computer-aided diagnosis (CAD) systems help in the detection of abnormal tissue. Microcalcifications can be an early indication of breast cancer. This work describes the implementation of a new method for the detection of microcalcifications in mammographies. The images were obtained from the mini-MIAS database. In the proposed method, the images are preprocessed using an x and y gradient operators, the output of each filter is the input of a fuzzy system that will detect areas with high-tone variation. The next step consists of a cellular automaton that uses a set of local rules to eliminate noise and keep the pixels with higher probabilities of belonging to a microcalcification region. Comparative results are presented.


Breast cancer Microcalcification Mammography image Image enhancement Fuzzy system Cellular automata 



We thank Instituto Politécnico Nacional (IPN), the Commission of Operation and Promotion of Academic Activities of IPN (COFAA), and the Mexican National Council of Science and Technology (CONACYT) for supporting our research activities.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Yoshio Rubio
    • 1
    Email author
  • Oscar Montiel
    • 1
  • Roberto Sepúlveda
    • 1
  1. 1.Instituto Politécnico NacionalCentro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN)TijuanaMexico

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