Modified Radial Basis Function Network for Brain Tumor Classification

被引：0

作者：

Deepa, S. N. ^{[1
]}

Devi, B. Aruna ^{[1
]}

机构：

[1] Anna Univ Technol, Dept EEE, Coimbatore 641037, Tamil Nadu, India

来源：

SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, PT I | 2011年 / 7076卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The study proposes a modified RBF with better network learning, convergence, error rates and classification results which involves spatial information data points using Gaussian Mixture Model (GMM) and Expectation Maximization (EM) algorithm for automatic biomedical brain tumour detection. The model was used to predict the brain tumour type (benign or malignant). The results showed outperformance of GMM-EM model with spatial points than the standard RBF model. A classification with a success of 85% and 90.3% has been obtained by the classifiers for RBF and RBF-GMM model.

引用

页码：366 / 371

页数：6

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