Radial Basis Function Neural Network Based Classifier For Diagnosing Of MCIAD Using Multimodal Neuroimaging

Neuroimaging has played a very important role in the diagnosis of brain degeneration disorders such as Alzheimers disease AD and Mild Cognitive Impairment MCI. To identify different stages of Alzheimers 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.