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IFIP International Conference on Computer Science and its Applications

CIIA 2015: Computer Science and Its Applications pp 119–128Cite as

Comparison of Automatic Seed Generation Methods for Breast Tumor Detection Using Region Growing Technique

  • Conference paper

Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT,volume 456)

Abstract

Seeded Region Growing algorithm is observed to be successfully implemented as a segmentation technique of medical images. This algorithm starts by selecting a seed point and, growing seed area through the exploitation of the fact that pixels which are close to each other have similar features. To improve the accuracy and effectiveness of region growing segmentation, some works tend to automate seed selection step. In this paper, we present a comparative study of two automatic seed selection methods for breast tumor detection using seeded region growing segmentation. The first method is based on thresholding technique and the second method is based on features similarity. Each method is applied on two modalities of breast digital images. Our results show that seed selection method based on thresholding technique is better than seed selection method based on features similarity.

Keywords

  • Medical image segmentation
  • Medical informatics
  • Automatic seed selection
  • Region growing
  • Tumor detection

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Author information

Authors and Affiliations

  1. Department of Informatics, Labo LRI, Badji-Mokhtar Annaba University, P.O.Box 12, 23000, Annaba, Algeria

    Ahlem Melouah

Authors
  1. Ahlem Melouah
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Corresponding author

Correspondence to Ahlem Melouah .

Editor information

Editors and Affiliations

  1. Tahar Moulay University, Saida, Algeria

    Abdelmalek Amine

  2. LIAS/ISAE-ENSMA, Chasseneuil, France

    Ladjel Bellatreche

  3. Sidi Bel Abbès University, Sidi Bel Abbès, Algeria

    Zakaria Elberrichi

  4. University of Vienna, Vienna, Austria

    Erich J. Neuhold

  5. Poznan University of Technology Inst. Computing Science, Poznan, Poland

    Robert Wrembel

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Melouah, A. (2015). Comparison of Automatic Seed Generation Methods for Breast Tumor Detection Using Region Growing Technique. In: Amine, A., Bellatreche, L., Elberrichi, Z., Neuhold, E., Wrembel, R. (eds) Computer Science and Its Applications. CIIA 2015. IFIP Advances in Information and Communication Technology, vol 456. Springer, Cham. https://doi.org/10.1007/978-3-319-19578-0_10

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  • DOI: https://doi.org/10.1007/978-3-319-19578-0_10

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19577-3

  • Online ISBN: 978-3-319-19578-0

  • eBook Packages: Computer ScienceComputer Science (R0)