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    RMCA-LSA: A Method of Monkey Brain Extraction

    Hongxia Deng1, Chunxiang Hu1, Zihao Zhou2, Jinxiu Guo1, Zhenxuan Zhang3, Haifang Li1,*

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 387-402, 2021, DOI:10.32604/iasc.2021.016989

    Abstract The traditional level set algorithm selects the position of the initial contour randomly and lacks the processing of edge information. Therefore, it cannot accurately extract the edge of the brain tissue. In order to solve this problem, this paper proposes a level set algorithm that fuses partition and Canny function. Firstly, the idea of partition is fused, and the initial contour position is selected by combining the morphological information of each region, so that the initial contour contains more brain tissue regions, and the efficiency of brain tissue extraction is improved. Secondly, the canny operator is fused in the energy… More >

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