Application Kernel Modified Fuzzy C-Means for gliomatosis cerebri
Andi Wulan, Melati Vidi Jannati, Zuherman Rustam, Ahmad Afif Fauzan · 2016
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.