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Microcalcification Detection in Mammograms Based on Fuzzy Logic and Cellular Automata

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Nature-Inspired Design of Hybrid Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 667))

Abstract

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.

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Acknowledgments

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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Authors and Affiliations

  1. Instituto Politécnico Nacional, Centro de Investigación y Desarrollo de Tecnología Digital (CITEDI-IPN), Av. Del Parque no. 1310, Mesa de Otay, 22510, Tijuana, B.C., Mexico

    Yoshio Rubio, Oscar Montiel & Roberto Sepúlveda

Authors
  1. Yoshio Rubio
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  2. Oscar Montiel
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  3. Roberto Sepúlveda
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Correspondence to Yoshio Rubio .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Oscar Castillo

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Rubio, Y., Montiel, O., Sepúlveda, R. (2017). Microcalcification Detection in Mammograms Based on Fuzzy Logic and Cellular Automata. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_38

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  • DOI: https://doi.org/10.1007/978-3-319-47054-2_38

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