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Application of Improved FCM Algorithm in Brain Image Segmentation

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 516))

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Abstract

Aiming at the problems of fuzzy c-means clustering (FCM) and its improved algorithms for MRI image segmentation, this paper proposes a new FCM algorithm based on neighborhood pixel correlation. The algorithm works out the influence degree of the neighborhood pixels on the central pixel by the correlation of the gray-level difference between the domain pixel and the center pixel. Then, the distance between the neighborhood pixel and the cluster center is used to control the membership of the center pixel, the improved algorithm will solve the existing influence factors of unification, ignoring the difference between pixels, resulting in inaccuracy of segmentation results. At last, this algorithm is implemented by MATLAB tool and compared with FCMS and FLICM algorithms. The feasibility of the presented algorithm and the accuracy of the segmentation result are verified by evaluating the algorithm and the experimental results according to the relevant evaluation criteria.

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Acknowledgments

Fundamental Research Funds for the Central Universities (No. 3132018194). Project name: Research on Ship Scheduling Method Based on Swarm Intelligence Hybrid Optimization Algorithm.

Author information

Authors and Affiliations

  1. College of Information Science and Technology, Dalian Maritime University, Dalian City, Liaoning Province, China

    Manzhuo Yin, Jinghuan Guo, Yuankun Chen & Yong Mu

Authors
  1. Manzhuo Yin
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  2. Jinghuan Guo
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  3. Yuankun Chen
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  4. Yong Mu
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Corresponding author

Correspondence to Jinghuan Guo .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Yin, M., Guo, J., Chen, Y., Mu, Y. (2020). Application of Improved FCM Algorithm in Brain Image Segmentation. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_4

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  • DOI: https://doi.org/10.1007/978-981-13-6504-1_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6503-4

  • Online ISBN: 978-981-13-6504-1

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