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A Survey on Segmentation Techniques of Mammogram Images

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Advances in Ubiquitous Networking 2 (UNet 2016)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 397))

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Abstract

Mammogram images are important tools allowing visualization of various types of breast cancer. In fact, cancer detection refers to the extraction of region of interest ROI, which represents the tumor, in the mammogram image. In medical imaging field, Computer Aided Diagnosis systems (CAD) are used to analyze this type of images. To extract region of interest from mammograms, image segmentation methods have been wildly applied. These methods consist of partitioning the image on meaningful regions or segments easy to analyze. There are various techniques and methods of segmentation of mammogram images in the literature. In this paper, we present a survey of different approaches of segmentation that we compared theoretically in terms of advantages and drawbacks, particulary for mammogram images.

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Authors and Affiliations

  1. Systems Architecture, ENSEM, Hassan II University, Casablanca, Morocco

    Ilhame Ait lbachir, Rachida Es-salhi, Imane Daoudi, Saida Tallal & Hicham Medromi

Authors
  1. Ilhame Ait lbachir
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  2. Rachida Es-salhi
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  3. Imane Daoudi
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  4. Saida Tallal
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  5. Hicham Medromi
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Corresponding author

Correspondence to Ilhame Ait lbachir .

Editor information

Editors and Affiliations

  1. Computer Science Laboratory (LIA), University of Avignon, Avignon, France

    Rachid El-Azouzi

  2. Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Daniel Sadoc Menasche

  3. Hassan II University of Casablanca, ENSEM, Casablanca, Morocco

    Essaïd Sabir

  4. CREATE-NET, Trento, Italy

    Francesco De Pellegrini

  5. INPT, Rabat, Morocco

    Mustapha Benjillali

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© 2017 Springer Science+Business Media Singapore

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Ait lbachir, I., Es-salhi, R., Daoudi, I., Tallal, S., Medromi, H. (2017). A Survey on Segmentation Techniques of Mammogram Images. In: El-Azouzi, R., Menasche, D.S., Sabir, E., De Pellegrini, F., Benjillali, M. (eds) Advances in Ubiquitous Networking 2. UNet 2016. Lecture Notes in Electrical Engineering, vol 397. Springer, Singapore. https://doi.org/10.1007/978-981-10-1627-1_43

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  • DOI: https://doi.org/10.1007/978-981-10-1627-1_43

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1626-4

  • Online ISBN: 978-981-10-1627-1

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