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A fuzzy theory-based MRI segmentation model

机译:基于模糊理论的MRI分割模型

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摘要

This paper proposes a fuzzy theory based Magnetic resonance imaging (MRI) segmentation model. MRI is an imaging technique used in radiology to form pictures of the anatomy and the physiological processes. However, it is very difficult to carry out the MRI image segmentation. In order to address these difficulties, this paper proposes a fuzzy theory based MRI segmentation approach. The boundary is defined by the fuzzy theory so that different cluster with image gray could be clearly identified. Based on the identification, iterations could be conducted to optimize the objective function which is used for measuring the cluster center of the images. Experiments are carried out to validate the proposed approach.
机译:本文提出了一种基于模糊理论的磁共振成像(MRI)分割模型。 MRI是一种用于放射学中的成像技术,用于形成解剖结构和生理过程的图片。但是,进行MRI图像分割非常困难。为了解决这些困难,本文提出了一种基于模糊理论的MRI分割方法。边界是由模糊理论定义的,因此可以清楚地识别出具有图像灰度的不同聚类。基于该识别,可以进行迭代以优化用于测量图像的聚类中心的目标函数。进行实验以验证所提出的方法。

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