Abstract
Alzheimer' s disease is the most common kind of dementia without effective treatment. Via early diagnosis, early intervention after diagnosis is the most effective way to handle this disease. However, the early diagnosis method remains to be studied. Neuroimaging data can provide a convenient measurement for the brain function and structure. Brain structure network is a good reflection of the fiber structural connectivity patterns between different brain cortical regions, which is the basis of brain's normal psychology function. In the paper, a brain structure network based on pattern recognition analysis was provided to realize an automatic diagnosis research of Alzheimer's disease and gray matter based on structure information. With the feature selection in pattern recognition, this method can provide the abnormal regions of brain structural network. The research in this paper analyzed the patterns of abnormal structural network in Alzheimer's disease from the aspects of connectivity and node, which was expected to provide updated information for the research about the pathological mechanism of Alzheimer's disease.