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Application of Wavelet De-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 549))

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Abstract

Recent advances in the field of image processing have revealed that the level of noise in mammogram images highly affect the images quality and classification performance of the classifiers. Whilst, numerous data mining techniques have been developed to achieve high efficiency and effectiveness for computer aided diagnosis systems. However, fuzzy soft set theory has been merely experimented for medical images. Thus, this study proposed a classifier based on fuzzy soft set with embedding wavelet de-noising filters. Therefore, the proposed methodology involved five steps namely: MIAS dataset, wavelet de-noising filters hard and soft threshold, region of interest identification, feature extraction and classification. Therefore, the feasibility of fuzzy soft set for classification of mammograms images has been scrutinized. Experimental results show that proposed classifier FussCyier provides the classification performance with Daub3 (Level 1) with accuracy 75.64% (hard threshold), precision 46.11%, recall 84.67%, F-Micro 60%. Thus, the results provide an alternative technique to categorize mammogram images.

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Acknowledgment

The authors would like to thank office for Research, Innovation, Commercialization and Consultancy Management (ORICC) and Universiti Tun Hussein Onn Malaysia for supporting this research under Vote U110.

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Authors and Affiliations

  1. Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Batu Pahat, 86400, Parit Raja, Johor, Malaysia

    Saima Anwar Lashari, Rosziati Ibrahim & Norhalina Senan

  2. Faculty of Computer Science and Information Technology, University of Malaya, Lembah Pantai, 50603, Kuala Lumpur, Malaysia

    Iwan Tri Riyadi Yanto & Tutut Herawan

Authors
  1. Saima Anwar Lashari
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  2. Rosziati Ibrahim
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  3. Norhalina Senan
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  4. Iwan Tri Riyadi Yanto
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  5. Tutut Herawan
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Correspondence to Saima Anwar Lashari .

Editor information

Editors and Affiliations

  1. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Rozaida Ghazali

  3. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Nazri Mohd Nawi

  4. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

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Lashari, S.A., Ibrahim, R., Senan, N., Yanto, I.T.R., Herawan, T. (2017). Application of Wavelet De-noising Filters in Mammogram Images Classification Using Fuzzy Soft Set. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_53

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51279-2

  • Online ISBN: 978-3-319-51281-5

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