计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 198-201.doi: 10.11896/j.issn.1002-137X.2017.6A.045
张辉,朱家明,唐文杰
ZHANG Hui, ZHU Jia-ming and TANG Wen-jie
摘要： 针对医学图像中通常伴有噪声、多目标的问题,传统水平集无法将图像中的多目标完全分割出来,提出了基于抑制式模糊聚类算法的改进型双水平集模型。首先,利用聚类算法对医学图像进行预分割降噪,通过标准化互信息准则(NMI)判断聚类是否达到满意效果,进而改良聚类算法,再由增加惩罚项的改进型双水平集进行二次分割。实验结果表明,该方法能够降低图像的噪声和算法的敏感性,水平集无需重新初始化,大大减少了计算量和迭代次数,该模型能将伴有噪声的多目标医学图像完全分割出来,获得了预期的分割效果。
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