Extension Neural Network Approach to Classification of Brain MRI
Chuin-Mu Wang, Ming-Ju Wu, Jianhong Chen, Cheng-Yi Yu · 2009
Magnetic resonance image (MRI) has been widely used for clinical applications in recent years. With the ability of scanning the same section by multiple frequencies, MRI makes it possible to generate several images on the same section. Despite of accessible abundant information, MRI also makes it more difficult to judge the location of every tissue. MRI will complicate the judgment due to strong noise. In order to resolve this problem, this paper endeavors to classify them via the help of extension neural network (ENN), This paper has to demonstrate the advantages of extension theory, statistical theory is considered as a judgment method, whereby obtaining experimental data of extension neural network and perceptron for subsequent comparison. It has proved that extension is superior to the other algorithms in terms of classification.