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A Modified Fuzzy C-Means Algorithm with Symmetry Information for MR Brain Image Segmentation

机译:带有对称信息的改进型模糊C均值算法用于MR脑图像分割

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摘要

In this paper, we present a novel modified Fuzzy Cmeans algorithm with symmetry information to reduce the effect of noise in brain tissue segmentation in magnetic resonance image (MRI). We integrate brain's bilateral symmetry into the conventional Fuzzy C-means (FCM) as an additional term. In experiments, some synthetic images, and both simulated and real brain images were used to investigate the robustness of the method against noise. Finally, the method was compared with the conventional FCM algorithm. Results show the viability of the approach and the preliminary investigation appears promising.
机译:在本文中,我们提出了一种新颖的带有对称信息的改进的Fuzzy Cmeans算法,以减少噪声在磁共振图像(MRI)中脑组织分割中的影响。作为附加术语,我们将大脑的双边对称性整合到常规的模糊C均值(FCM)中。在实验中,一些合成图像以及模拟和真实的大脑图像都被用来研究该方法抗噪声的鲁棒性。最后,将该方法与常规FCM算法进行了比较。结果表明该方法的可行性,初步研究似乎很有希望。

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