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Fuzzy C-means Clustering with Bilateral Filtering for Medical Image Segmentation

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Book cover Hybrid Artificial Intelligent Systems (HAIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7208))

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Abstract

Fuzzy c-means (FCM) is a widely used unsupervised pattern recognition method for medical image segmentation. The conventional FCM algorithm and some existing variants are either sensitive to noise or prone to loss of details. This paper presents a modified FCM algorithm that incorporates bilateral filtering for medical image segmentation. The experimental results and quantitative analyses suggest that, compared to the conventional FCM, the proposed method improves clustering performance with higher standard of noise-resistance and detail-preservation.

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Author information

Authors and Affiliations

  1. Shanghai Key Laboratory of Scalable Computing and Systems, School of Software, Shanghai Jiao Tong University, Shanghai, China

    Yuchen Liu, Kai Xiao, Alei Liang & Haibing Guan

Authors
  1. Yuchen Liu
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  2. Kai Xiao
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  3. Alei Liang
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  4. Haibing Guan
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Editor information

Editors and Affiliations

  1. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VŠB-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs(MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, 120-749, Seoul, Korea

    Sung-Bae Cho

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© 2012 Springer-Verlag Berlin Heidelberg

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Liu, Y., Xiao, K., Liang, A., Guan, H. (2012). Fuzzy C-means Clustering with Bilateral Filtering for Medical Image Segmentation. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_20

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  • DOI: https://doi.org/10.1007/978-3-642-28942-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28941-5

  • Online ISBN: 978-3-642-28942-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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