Analysis of Alzheimer Condition in T1-Weighted MR Images using Texture Features and SVM Classifier

Alzheimer’s is the most common neurodegenerative disease, which affect memory, thinking, behavior and emotion. The imaging modality is Magnetic resonance imaging (MRI), whichis non-invasive technique and describes the pathology of the three-dimensional brain structure for finding the Alzheimer's disease (AD). Texture features were extracted by utilizing SF, SGLDM, GLDS, NGTDM, SFM, Laws TEM, Fourier, Fractal and Shape based feature techniques. To identify the Alzheimer's disease three classifiers k nearest neighbor, support vector machine was used. SVM Classifier Accuracy, Sensitivity and Specificity respectively increased when compare with KNN classifier.