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Medical image segmentation using improved FCM

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Abstract

Image segmentation is one of the most important problems in medical image processing, and the existence of partial volume effect and other phenomena makes the problem much more complex. Fuzzy C-means, as an effective tool to deal with PVE, however, is faced with great challenges in efficiency. Aiming at this, this paper proposes one improved FCM algorithm based on the histogram of the given image, which will be denoted as HisFCM and divided into two phases. The first phase will retrieve several intervals on which to compute cluster centroids, and the second one will perform image segmentation based on improved FCM algorithm. Compared with FCM and other improved algorithms, HisFCM is of much higher efficiency with satisfying results. Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second, and can satisfy real-time requirements of medical image processing.

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Authors and Affiliations

  1. School of Computer Science and Technology, Shandong University, Jinan, 250101, China

    XiaoFeng Zhang, CaiMing Zhang, WenJing Tang & ZhenWen Wei

  2. School of Information and Electrical Engineering, Ludong University, Yantai, 264025, China

    XiaoFeng Zhang & WenJing Tang

  3. School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, 250014, China

    CaiMing Zhang

  4. Shandong Province Key Lab of Digital Media Technology, Jinan, 250014, China

    CaiMing Zhang

Authors
  1. XiaoFeng Zhang
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  2. CaiMing Zhang
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  3. WenJing Tang
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  4. ZhenWen Wei
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Correspondence to CaiMing Zhang.

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Zhang, X., Zhang, C., Tang, W. et al. Medical image segmentation using improved FCM. Sci. China Inf. Sci. 55, 1052–1061 (2012). https://doi.org/10.1007/s11432-012-4556-0

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  • DOI: https://doi.org/10.1007/s11432-012-4556-0

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