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Antlion Optimization Based Segmentation for MRI Liver Images

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Genetic and Evolutionary Computing (ICGEC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 536))

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Abstract

This paper proposes an approach for liver segmentation, depending on Antlion optimization algorithm. It is used as a clustering technique to accomplish the segmentation process in MRI images. Antlion optimization algorithm is combined with a statistical image of liver to segment the whole liver. The segmented region of liver is improved using some morphological operations. Then, mean shift clustering technique divides the segmented liver into a number of regions of interest (ROIs). Starting with Antlion algorithm, it calculates the values of different clusters in the image. A statistical image of liver is used to get the potential region that liver might exist in. Some pixels representing the required clusters are picked up to get the initial segmented liver. Then the segmented liver is enhanced using morphological operations. Finally, mean shift clustering technique divides the liver into different regions of interest. A set of 70 MRI images, was used to segment the liver and test the proposed approach. Structural Similarity index (SSIM) validates the success of the approach. The experimental results showed that the overall accuracy of the proposed approach, results in 94.49 % accuracy.

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Author information

Authors and Affiliations

  1. Institute of Statistical Studies and Research, Cairo University, Cairo, Egypt

    Abdalla Mostafa & Hesham Hefny

  2. Radiology Department, National Liver Institute, Menofia University, Shibin Al Kawm, Al Minufiyah, Egypt

    Mohamed Houseni & Naglaa Allam

  3. Faculty of Computers and Information, Cairo University, Cairo, Egypt

    Aboul Ella Hassanien

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, China

    Pei-Wei Tsai

  5. Scientific Research Group in Egypt (SRGE), Cairo, Egypt

    Aboul Ella Hassanien

Authors
  1. Abdalla Mostafa
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  2. Mohamed Houseni
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  3. Naglaa Allam
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  4. Aboul Ella Hassanien
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  5. Hesham Hefny
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  6. Pei-Wei Tsai
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Corresponding author

Correspondence to Abdalla Mostafa .

Editor information

Editors and Affiliations

  1. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Jeng-Shyang Pan

  2. School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Chia-Hung Wang

  4. College of Information Science and Engineering, Fujian University of Technology, Fuzhou, Fujian, China

    Xin Hua Jiang

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Mostafa, A., Houseni, M., Allam, N., Hassanien, A.E., Hefny, H., Tsai, PW. (2017). Antlion Optimization Based Segmentation for MRI Liver Images. In: Pan, JS., Lin, JW., Wang, CH., Jiang, X. (eds) Genetic and Evolutionary Computing. ICGEC 2016. Advances in Intelligent Systems and Computing, vol 536. Springer, Cham. https://doi.org/10.1007/978-3-319-48490-7_31

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  • DOI: https://doi.org/10.1007/978-3-319-48490-7_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48489-1

  • Online ISBN: 978-3-319-48490-7

  • eBook Packages: EngineeringEngineering (R0)

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