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IJSTR >> Volume 5 - Issue 4, April 2016 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Radial Basis Function Neural Network Based Classifier For Diagnosing Of MCI/AD Using Multimodal Neuroimaging

[Full Text]



R.Ramya, S.P.Sivagnana Subramanian, ADNI



Image Registration, Feature Extraction, Radial basis function neural network, performance evaluation.



Neuroimaging has played a very important role in the diagnosis of brain degeneration disorders, such as Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI). To identify different stages of Alzheimer’s disease and efficient analysis system has been developed for magnetic resonance Imaging (MRI) and positron emission tomography (PET) Neuroimages using radial basis function neural network (RBFNN) classifier.Normal, MCI and AD identification by using RBFNN classifier. The proposed model performance was assessed based on three parameters such as sensitivity, specificity and accuracy.



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