ROI Analysis Using Harvard-Oxford Atlas in Alzheimer’s Disease Diagnosis Based on PCA

Alzheimer's disease (AD) is characterized by impaired glucose metabolism and can be detected using Positron Emission Tomography (PET) neuroimaging. In this study, an automatic method for diagnosis of ADbased on region of interest (ROI) is presented. First, subject’s PET neuroimage is automatically parcellated into48 predefined ROIs using Harvard-Oxford structural Atlas. The most discriminative regions are discoveredusing principal component analysis (PCA). Based on features extracted using PCA, support vector machines are adapted to discriminate normal control (NC) from AD. For classification of AD from NC, the proposed method achieves 89.14% of classification accuracy; while the accuracy of Automated Anatomical Labeling (AAL)-based approach is only 80.68%.

کلیدواژه ها:

Alzheimer ، Principal component analysis ، Positron emission