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Adaptive trapezoid region intercept histogram based Otsu method for brain MR image segmentation

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Abstract

In brain magnetic resonance (MR) image segmentation, the current Otsu method is often difficult to take both accuracy and anti-noise capability into consideration. So, in this paper, an adaptive trapezoid region intercept histogram based Otsu method is proposed. On the basis of bilateral filtering, the method uses Sigmoid function to identify the noise and adaptively calculate the weight of neighborhood pixel, and then constructs a 2D histogram of gray value-adaptive weight neighborhood gray mean to enhance the algorithm’s anti-noise capability and detail retention. The hierarchical threshold model is adopted: the macro-threshold T1 is determined by the trapezoid region intercept histogram based Otsu method, and the micro-threshold T2 is determined by the between-class variance criterion again in the trapezoid region corresponding to T1. The image is segmented by T2 to improve the accuracy of image segmentation. Based on the neighborhood information, an adaptive parameter l is designed to identify and correct noise, thus enhancing the universality of the algorithm. The experimental results show that the proposed method is effective and can be well applied to MR image segmentation.

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Acknowledgements

This work was supported by Hunan Provincial Natural Science Foundation (No. 2020JJ4587), Guangdong Basic and Applied Basic Research Foundation (No. 2019A1515110423), and the Degree and Postgraduate Education Reform Project of Hunan Province (No. 2019JGYB115).

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Authors and Affiliations

  1. School of Information Technology and Management, Hunan University of Finance and Economics, Changsha, 410205, China

    Leyi Xiao & Chaodong Fan

  2. Foshan Green Intelligent Manufacturing Research Institute of Xiangtan University, Foshan, 528000, China

    Chaodong Fan

  3. College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China

    Honglin Ouyang

  4. University of Salerno, Fisciano, Italy

    Andrea F. Abate

  5. School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan, 430073, China

    Shaohua Wan

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  1. Leyi Xiao
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Correspondence to Shaohua Wan.

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Xiao, L., Fan, C., Ouyang, H. et al. Adaptive trapezoid region intercept histogram based Otsu method for brain MR image segmentation. J Ambient Intell Human Comput 13, 2161–2176 (2022). https://doi.org/10.1007/s12652-021-02976-6

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  • DOI: https://doi.org/10.1007/s12652-021-02976-6

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