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广义模糊Gibbs随机场与MR图像分割算法研究

DOI: 10.11834/jig.200509199

Keywords: 广义模糊集,广义模糊Gibbs随机场,图像分割,部分容积效应

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Abstract:

为了对图像进行准确、可靠的分割,提出了一种基于广义模糊集的软分割算法,并将广义模糊集和Gibbs场结合起来,提出了广义模糊Gibbs随机场模型,同时建立了广义模糊Gibbs分割(GFGS)算法。该算法是首先把每一个分割类看作是广义模糊类,并以最大后验概率(MAP)为判别准则来决定每一个像素值的归类以及它属于该类的隶属度;然后用广义隶属度函数中负的部分来刻划数据中的异常值,使得该算法能有效地处理异常值;最后用该模糊类的质心来更新类的中心,并以人脑的仿真图像和临床MR图像进行了实验。实验结果表明,该算法能有效地滤除噪声和处理部分容积效应,是一个分割能力强、稳健性好的算法。

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