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Application Kernel Modified Fuzzy C-Means for gliomatosis cerebri

机译:应用核修饰的模糊C均值在脑胶质瘤病中的应用

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Differences in treatment of gliomatosis cerebri and brain infection are crucial to the healing process. Nowadays, Magnetic Resonance Spectroscopy (MRS) is used to determine the content of metabolites in patients with glioma (astrocytoma) or brain infection. An analysis of the MRS cannot be used as a reference for determining whether a patient suffering from brain glioma or brain infection. This paper discusses the process of classifying the MRS data to determine the disease suffered by a patient. The ultimate purpose of this paper is to determine MRS data classification accuracy using Modified Kernel Fuzzy C-Means. Modified Kernel Fuzzy C-Means is the refinement of Fuzzy C-Means and uses kernel function as the distance measure. The accuracy of the classification is very dependent on the parameters in the Kernel Modified Fuzzy C-Means algorithm.
机译:脑胶质瘤病和脑部感染的治疗差异对愈合过程至关重要。如今,磁共振波谱(MRS)用于确定神经胶质瘤(星形细胞瘤)或脑部感染患者的代谢物含量。 MRS的分析不能用作确定患者是否患有脑胶质瘤或脑部感染的参考。本文讨论了对MRS数据进行分类以确定患者所患疾病的过程。本文的最终目的是使用改进的核模糊C均值确定MRS数据分类的准确性。改进的核模糊C均值是对模糊C均值的改进,并使用核函数作为距离度量。分类的准确性非常取决于内核修改的模糊C均值算法中的参数。

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