Application Kernel Modified Fuzzy C-Means for Gliomatosis Cerebri

被引:0
作者
Wulan, Andi [1 ]
Jannati, Melati Vidi [1 ]
Rustam, Zuherman [1 ]
Fauzan, Ahmad Afif [1 ]
机构
[1] Univ Indonesia, Dept Math, Depok 16424, Indonesia
来源
2016 12TH INTERNATIONAL CONFERENCE ON MATHEMATICS, STATISTICS, AND THEIR APPLICATIONS (ICMSA) | 2016年
关键词
classification cancer; kernel function; modified fuzzy C-means; gliomatosis cerebri;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
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.
引用
收藏
页码:35 / 38
页数:4
相关论文
共 12 条
  • [1] [Anonymous], 2010, Putting the Spin in CFD
  • [2] [Anonymous], Pattern Recognition with Fuzzy Objective Function Algorithms, DOI 10.1007/978-1-4757-0450-1_3
  • [3] Berstein M., 2000, NEUROONCOLOGY ESSENT
  • [4] CRISTIANINI N, 2000, INTRO SVMS OTHER KER
  • [5] Eyasigomari, 2015, APPL SOFT COMPUT, V35, P4351
  • [6] Fauzan A. A., 2015, APLIKASI MODIFIED FU
  • [7] Fikri A., 2010, PROS SEM NAS MAT 201, P1
  • [8] Jayasuriya, 2013, MODIFIED FUZZY C MEA
  • [9] Nonlinear component analysis as a kernel eigenvalue problem
    Scholkopf, B
    Smola, A
    Muller, KR
    [J]. NEURAL COMPUTATION, 1998, 10 (05) : 1299 - 1319
  • [10] Vapnik VN., 1998, STAT LEARNING THEORY