SIGNIFICANT REGION-BASED FRAMEWORK FOR EARLY DIAGNOSIS OF ALZHEIMER'S DISEASE USING ~(11)C PIB-PET SCANS

摘要

Alzheimer's disease (AD) is a behavioral and cognitive neurodegenerative disorder whose sufferers exceed 5.5 million Americans. Among its stages, the early diagnosis of AD is considered the main research issue due to many factors including the variable effects of the disease through its patients. This paper targets the personalized diagnosis of AD through presenting a local/regional analysis system that represents the degree of regional abnormalities using detailed parcellation of the brain. For more detailed results, the statistical analysis was applied for restricting the diagnosis to the statistically determined significant brain regions. The system's evaluation shows promising results with an average accuracy, specificity, and sensitivity between the three tested groups of 98%, 99.09%, and 96.48%, respectively.