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Application of fractal theory and fuzzy enhancement in ultrasound image segmentation

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Abstract

The manuscript describes an ultrasound image segmentation technique based on the fractional Brownian motion (FBM) model. Here, the ultrasound images are first enhanced using a fuzzy-based technique, and later the FBM model is employed to obtain the fractal features used for segmentation. The novelty lies in combining the fuzzy-enhancement technique and FBM model, and further illustrating that fractal length-based segmentation provides better results than fractal dimension-based segmentation. Experimental results on ultrasound images of carotid artery clearly illustrate that the segmentation outputs obtained from fractal length are superior, and the high qualitative values of DSC, Precision, Recall and F1 score (0.9617, 0.9629, 0.9653 and 0.9641 respectively), together with a low value of APD (1.9316), indicate that the proposed method is comparable to other state-of-the-art segmentation techniques.

Summary of proposed technique — overall design flow.

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Acknowledgements

This research was financially supported by the Foundation of China (No.61471228), the Key Project of Guangdong Province Science & Technology Plan (No. 2015B020233018), and the Scientific Research Grant of Shantou University, China, Grant No: NTF17016.

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Authors and Affiliations

  1. Department of Electronic Engineering, Shantou University, Shantou, Guangdong, China

    Zhemin Zhuang, Naihai Lei & Alex Noel Joseph Raj

  2. Imaging Department, First Hospital of Medical College of Shantou University, Shantou, Guangdong, China

    Shunmin Qiu

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  1. Zhemin Zhuang
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  2. Naihai Lei
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  3. Alex Noel Joseph Raj
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  4. Shunmin Qiu
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Correspondence to Alex Noel Joseph Raj.

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Zhuang, Z., Lei, N., Joseph Raj, A.N. et al. Application of fractal theory and fuzzy enhancement in ultrasound image segmentation. Med Biol Eng Comput 57, 623–632 (2019). https://doi.org/10.1007/s11517-018-1907-z

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  • DOI: https://doi.org/10.1007/s11517-018-1907-z

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